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08.09.2012 - Pascaline Dupas
08.09.2012 - Pascaline Dupas
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08.09.2012 - Pascaline Dupas

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Price Subsidies, Diagnostic Tests adn the Targeting of Malaria Treatment

Price Subsidies, Diagnostic Tests adn the Targeting of Malaria Treatment

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  • 1. Price Subsidies, Diagnostic Tests and the Targeting of Malaria Treatment Jessica Cohen Pascaline Dupas Simone Schaner Harvard Stanford Dartmouth IFPRI, August 2012Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 2. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 3. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 4. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 5. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 6. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 7. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 8. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 9. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 10. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 11. Introduction Limiting the spread of infectious disease is a public good Prevention and treatment products should be subsidized (Pigou) But in the presence of heterogeneous returns: tradeo between access and targeting Overuse is bad if there is a budget constraint (wasted subsidy dollars) But its even worse if there are negative social spillovers E.g. use of antibiotics to treat viral infections contributes to antibiotic resistance Likewise, antimalarial treatment in the absence of malaria can contribute to antimalarial resistance Trade-o between aordability today and eectiveness in the future Prescription-only drugs Dicult to enforce when weak governance, lack of doctors Supply Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 12. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 13. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 14. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 15. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 16. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 17. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 18. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 19. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 20. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 21. This Paper: Subsidies for Malaria Treatment Malaria = 1 million deaths every year New drug called ACT = Artemisinin Combination Therapy Combines Artemisinin with a partner drug to slow resistance development Problem: Unaordable for most (Kenya: $6.25 to treat adult, $1.56 to treat infant) Global Fund AMFm: Reduce price of over-the-counter ACTs by 92-95 percent 1. Improve access and save lives 2. Fight resistance to artemisinin (by crowding out monotherapy) Potential problem: risk of overtreatment Drug Resistance Wasted subsidy dollars (pilot in 7 countries = $240M in just over a year) Delays in learning about eectiveness of ACT (Adhvaryu, 2012) Delays in appropriate treatment Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 22. This Paper 1. How worried should policy-makers be about overtreatment? A lot. At proposed ACT subsidy level (92%), only 39% of adults who take ACTs actually have malaria 2. Does it mean they shouldnt subsidize ACTs? They should. Without subisidy, ACT access is very low, especially among the poor. Children die. 3. So what should they do? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 23. This Paper 1. How worried should policy-makers be about overtreatment? A lot. At proposed ACT subsidy level (92%), only 39% of adults who take ACTs actually have malaria 2. Does it mean they shouldnt subsidize ACTs? They should. Without subisidy, ACT access is very low, especially among the poor. Children die. 3. So what should they do? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 24. This Paper 1. How worried should policy-makers be about overtreatment? A lot. At proposed ACT subsidy level (92%), only 39% of adults who take ACTs actually have malaria 2. Does it mean they shouldnt subsidize ACTs? They should. Without subisidy, ACT access is very low, especially among the poor. Children die. 3. So what should they do? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 25. This Paper 1. How worried should policy-makers be about overtreatment? A lot. At proposed ACT subsidy level (92%), only 39% of adults who take ACTs actually have malaria 2. Does it mean they shouldnt subsidize ACTs? They should. Without subisidy, ACT access is very low, especially among the poor. Children die. 3. So what should they do? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 26. This Paper 1. How worried should policy-makers be about overtreatment? A lot. At proposed ACT subsidy level (92%), only 39% of adults who take ACTs actually have malaria 2. Does it mean they shouldnt subsidize ACTs? They should. Without subisidy, ACT access is very low, especially among the poor. Children die. 3. So what should they do? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 27. This Paper 1. How worried should policy-makers be about overtreatment? A lot. At proposed ACT subsidy level (92%), only 39% of adults who take ACTs actually have malaria 2. Does it mean they shouldnt subsidize ACTs? They should. Without subisidy, ACT access is very low, especially among the poor. Children die. 3. So what should they do? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 28. This Paper Subsidize ACTs, but not as much as planned Elasticity of demand for ACTs is quite low at low prices ... and particularly low among those most likely to have malaria (children) ⇒ Screening eect of slightly higher ACT price Redirect some of the subsidy money towards subsidizing over-the-counter rapid diagnostic tests (RDTs) Very high willingness to experiment with RDTs Moving from the proposed 92% ACT subsidy to a 80% ACT subsidy + RDT subsidy⇒ increases the share of ACT takers who are malaria positive by 24 percentage points Could be even higher in the long-run once people trust RDT results Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 29. This Paper Subsidize ACTs, but not as much as planned Elasticity of demand for ACTs is quite low at low prices ... and particularly low among those most likely to have malaria (children) ⇒ Screening eect of slightly higher ACT price Redirect some of the subsidy money towards subsidizing over-the-counter rapid diagnostic tests (RDTs) Very high willingness to experiment with RDTs Moving from the proposed 92% ACT subsidy to a 80% ACT subsidy + RDT subsidy⇒ increases the share of ACT takers who are malaria positive by 24 percentage points Could be even higher in the long-run once people trust RDT results Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 30. This Paper Subsidize ACTs, but not as much as planned Elasticity of demand for ACTs is quite low at low prices ... and particularly low among those most likely to have malaria (children) ⇒ Screening eect of slightly higher ACT price Redirect some of the subsidy money towards subsidizing over-the-counter rapid diagnostic tests (RDTs) Very high willingness to experiment with RDTs Moving from the proposed 92% ACT subsidy to a 80% ACT subsidy + RDT subsidy⇒ increases the share of ACT takers who are malaria positive by 24 percentage points Could be even higher in the long-run once people trust RDT results Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 31. This Paper Subsidize ACTs, but not as much as planned Elasticity of demand for ACTs is quite low at low prices ... and particularly low among those most likely to have malaria (children) ⇒ Screening eect of slightly higher ACT price Redirect some of the subsidy money towards subsidizing over-the-counter rapid diagnostic tests (RDTs) Very high willingness to experiment with RDTs Moving from the proposed 92% ACT subsidy to a 80% ACT subsidy + RDT subsidy⇒ increases the share of ACT takers who are malaria positive by 24 percentage points Could be even higher in the long-run once people trust RDT results Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 32. This Paper Subsidize ACTs, but not as much as planned Elasticity of demand for ACTs is quite low at low prices ... and particularly low among those most likely to have malaria (children) ⇒ Screening eect of slightly higher ACT price Redirect some of the subsidy money towards subsidizing over-the-counter rapid diagnostic tests (RDTs) Very high willingness to experiment with RDTs Moving from the proposed 92% ACT subsidy to a 80% ACT subsidy + RDT subsidy⇒ increases the share of ACT takers who are malaria positive by 24 percentage points Could be even higher in the long-run once people trust RDT results Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 33. This Paper Subsidize ACTs, but not as much as planned Elasticity of demand for ACTs is quite low at low prices ... and particularly low among those most likely to have malaria (children) ⇒ Screening eect of slightly higher ACT price Redirect some of the subsidy money towards subsidizing over-the-counter rapid diagnostic tests (RDTs) Very high willingness to experiment with RDTs Moving from the proposed 92% ACT subsidy to a 80% ACT subsidy + RDT subsidy⇒ increases the share of ACT takers who are malaria positive by 24 percentage points Could be even higher in the long-run once people trust RDT results Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 34. This Paper Subsidize ACTs, but not as much as planned Elasticity of demand for ACTs is quite low at low prices ... and particularly low among those most likely to have malaria (children) ⇒ Screening eect of slightly higher ACT price Redirect some of the subsidy money towards subsidizing over-the-counter rapid diagnostic tests (RDTs) Very high willingness to experiment with RDTs Moving from the proposed 92% ACT subsidy to a 80% ACT subsidy + RDT subsidy⇒ increases the share of ACT takers who are malaria positive by 24 percentage points Could be even higher in the long-run once people trust RDT results Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 35. How did we generate these ndings? Field experiment in poor, rural, malaria-endemic area (Western Kenya) in 2009 Randomized ∼2,700 households into three policy regimes: No subsidy (status quo until a few months ago) Subsidy for ACT at the local drug shop (variation: 80-92 percent ⇒ $0.50-$1.25 to treat an adult) Subsidy for ACT + subsidy for Rapid Diagnostic Test (RDT) (85 percent ⇒ $0.19 to test) Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 36. Outline 1. Background: Treatment-Seeking Behavior in Rural Africa 2. Theoretical Framework 3. Experimental Design 4. Results 5. Conclusion Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 37. Baseline Treatment Seeking Behavior Three main options Go to health center / Go to drug shop / Do nothing Health center Can consult with trained health professional Microscopic testing available ( but: high rates of false negatives, test results largely ignored) RDTs introduced in few health centers ( but: quite rare) ACTs free to those who have malaria ( but: stockouts, long lines) Drug shop Not quite like CVS... No diagnostic testing available Drug shop sta doesnt have medical training Sell many antimalarials that vary in price and eectiveness Cheaper drugs (SP, AQ, etc) sub-therapeutic (parasite resistance has left them only partly eective) Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 38. Baseline Treatment Seeking Behavior Three main options Go to health center / Go to drug shop / Do nothing Health center Can consult with trained health professional Microscopic testing available ( but: high rates of false negatives, test results largely ignored) RDTs introduced in few health centers ( but: quite rare) ACTs free to those who have malaria ( but: stockouts, long lines) Drug shop Not quite like CVS... No diagnostic testing available Drug shop sta doesnt have medical training Sell many antimalarials that vary in price and eectiveness Cheaper drugs (SP, AQ, etc) sub-therapeutic (parasite resistance has left them only partly eective) Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 39. Baseline Treatment Seeking Behavior Three main options Go to health center / Go to drug shop / Do nothing Health center Can consult with trained health professional Microscopic testing available ( but: high rates of false negatives, test results largely ignored) RDTs introduced in few health centers ( but: quite rare) ACTs free to those who have malaria ( but: stockouts, long lines) Drug shop Not quite like CVS... No diagnostic testing available Drug shop sta doesnt have medical training Sell many antimalarials that vary in price and eectiveness Cheaper drugs (SP, AQ, etc) sub-therapeutic (parasite resistance has left them only partly eective) Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 40. Baseline Treatment-Seeking Behavior All Household Level Malaria and Diagnostic Incidence - Past Month # of Presumed Malaria Episodes 1.22 If Episode: Malaria Test 0.29 Provider Choice for All Presumed Malaria Episodes Health Center Visit 0.41 Drug Shop Visit 0.37 No Care 0.18 Medication for All Presumed Malaria Episodes No Antimalarial 0.22 ACT 0.21 SP, AQ, Other 0.35 Forgot Name 0.22 Cost Per Episode (Ksh) 131 Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 41. Outline 1. Background: Treatment-Seeking Behavior in Rural Africa 2. Theoretical Framework 3. Experimental Design 4. Results 5. Conclusion Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 42. Theoretical Framework Policy parameters of interest: The share of true malaria episodes that do not get treated with ACTs UT for under-treatment. The share of non-malaria episodes that are treated with ACTs OT for over-treatment. The objective of the social planner is to decrease UT while limiting the increase in OT Max f (UT , OT ), subject to a budget constraint A function that we focus on is fraction of ACT takers who are malaria positive: ( − UT ) Π T = (1 − UT 1 Π + OT (1 − Π) ) where Π represent the fraction of all illness episodes that are actually malaria. Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 43. Theoretical Framework Policy parameters of interest: The share of true malaria episodes that do not get treated with ACTs UT for under-treatment. The share of non-malaria episodes that are treated with ACTs OT for over-treatment. The objective of the social planner is to decrease UT while limiting the increase in OT Max f (UT , OT ), subject to a budget constraint A function that we focus on is fraction of ACT takers who are malaria positive: ( − UT ) Π T = (1 − UT 1 Π + OT (1 − Π) ) where Π represent the fraction of all illness episodes that are actually malaria. Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 44. Theoretical Framework Policy parameters of interest: The share of true malaria episodes that do not get treated with ACTs UT for under-treatment. The share of non-malaria episodes that are treated with ACTs OT for over-treatment. The objective of the social planner is to decrease UT while limiting the increase in OT Max f (UT , OT ), subject to a budget constraint A function that we focus on is fraction of ACT takers who are malaria positive: ( − UT ) Π T = (1 − UT 1 Π + OT (1 − Π) ) where Π represent the fraction of all illness episodes that are actually malaria. Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 45. Theoretical Framework Policy parameters of interest: The share of true malaria episodes that do not get treated with ACTs UT for under-treatment. The share of non-malaria episodes that are treated with ACTs OT for over-treatment. The objective of the social planner is to decrease UT while limiting the increase in OT Max f (UT , OT ), subject to a budget constraint A function that we focus on is fraction of ACT takers who are malaria positive: ( − UT ) Π T = (1 − UT 1 Π + OT (1 − Π) ) where Π represent the fraction of all illness episodes that are actually malaria. Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 46. Theoretical Framework Key questions: What are the derivatives of UT ,OT , and T with respect to the ACT subsidy level? the presence of RDTs in the retail sector? This will depend on: 1. How households decide where to go when someone falls sick with a suspected malaria infection, and how this is aected by the subsidy regimes Tradeos: convenience, cost, diagnostic services 2. How this varies with the households prior over whether or not the illness is malaria Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 47. Theoretical Framework Key questions: What are the derivatives of UT ,OT , and T with respect to the ACT subsidy level? the presence of RDTs in the retail sector? This will depend on: 1. How households decide where to go when someone falls sick with a suspected malaria infection, and how this is aected by the subsidy regimes Tradeos: convenience, cost, diagnostic services 2. How this varies with the households prior over whether or not the illness is malaria Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 48. Theoretical Framework Key questions: What are the derivatives of UT ,OT , and T with respect to the ACT subsidy level? the presence of RDTs in the retail sector? This will depend on: 1. How households decide where to go when someone falls sick with a suspected malaria infection, and how this is aected by the subsidy regimes Tradeos: convenience, cost, diagnostic services 2. How this varies with the households prior over whether or not the illness is malaria Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 49. Theoretical Framework Key questions: What are the derivatives of UT ,OT , and T with respect to the ACT subsidy level? the presence of RDTs in the retail sector? This will depend on: 1. How households decide where to go when someone falls sick with a suspected malaria infection, and how this is aected by the subsidy regimes Tradeos: convenience, cost, diagnostic services 2. How this varies with the households prior over whether or not the illness is malaria Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 50. Model Setup 1. Household gets an illness shock, generating a vector of symptoms. Objective probability of having malaria (π ). 2. Households can take one of three actions, a: Seek ACT treatment at the drug shop, a=s Seek diagnostic and treatment (ACT when appropriate) at the health center, a=h Do something else (nothing or buy other medication at drug shop) a=n 3. Value of action a given person is either malaria positive (P ) or negative (N ) is Vka , k ∈ {P , N } ⇒ Each action has expected value: V a ( π ) = π VP + ( 1 − π ) VN a a 4. Normalize: V n (π ) = 0 Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 51. Model Setup 1. Household gets an illness shock, generating a vector of symptoms. Objective probability of having malaria (π ). 2. Households can take one of three actions, a: Seek ACT treatment at the drug shop, a=s Seek diagnostic and treatment (ACT when appropriate) at the health center, a=h Do something else (nothing or buy other medication at drug shop) a=n 3. Value of action a given person is either malaria positive (P ) or negative (N ) is Vka , k ∈ {P , N } ⇒ Each action has expected value: V a (π ) = πVP + (1 − π ) VN a a 4. Normalize: V n (π ) = 0 Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 52. Model Setup 1. Household gets an illness shock, generating a vector of symptoms. Objective probability of having malaria (π ). 2. Households can take one of three actions, a: Seek ACT treatment at the drug shop, a=s Seek diagnostic and treatment (ACT when appropriate) at the health center, a=h Do something else (nothing or buy other medication at drug shop) a=n 3. Value of action a given person is either malaria positive (P ) or negative (N ) is Vka , k ∈ {P , N } ⇒ Each action has expected value: V a (π ) = πVP + (1 − π ) VN a a 4. Normalize: V n (π ) = 0 Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 53. Model Setup 1. Household gets an illness shock, generating a vector of symptoms. Objective probability of having malaria (π ). 2. Households can take one of three actions, a: Seek ACT treatment at the drug shop, a=s Seek diagnostic and treatment (ACT when appropriate) at the health center, a=h Do something else (nothing or buy other medication at drug shop) a=n 3. Value of action a given person is either malaria positive (P ) or negative (N ) is Vka , k ∈ {P , N } ⇒ Each action has expected value: V a (π ) = πVP + (1 − π ) VN a a 4. Normalize: V n (π ) = 0 Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 54. Possible Scenario Va(π) Vs(π) Vh(π) Vn(π) 0 π Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 55. Possible Scenario Va(π) Vs(π) Vh(π) Vn(π) 0 π Other Visits Health Center ACT at Drug Shop Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 56. Impact of ACT Subsidy Va(π) Vs(π) Vh(π) Vn(π) 0 π Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 57. Impact of ACT Subsidy Va(π) Vs(π) Vh(π) Vn(π) 0 π Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 58. Crowd-Out of Health Center Visits Va(π) Vs(π) Vh(π) Vn(π) 0 π ACT at Drug Shop Other Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 59. Very Poor Households Va(π) Vn(π) 0 Vh(π) Vs(π) π Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 60. Very Poor Households Va(π) Vn(π) 0 Vh(π) Vs(π) π Other Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 61. Very Poor Households: Impact of ACT Subsidy Va(π) Vs(π) Vn(π) 0 Vh(π) π Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 62. Crowd-out no care / subtherapeutic care Va(π) Vs(π) Vn(π) 0 Vh(π) π Other ACT at Drug Shop Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 63. Summary: -UT, +OT, T ambiguous Figure 1. Theoretical Treatment Seeking Scenarios A.  Rich  Households   B.  Poor  Households   Va(π) Va(π) Vs(π) Vn(π) 0 Vh(π) Vs(π) Vh(π) Vn(π) 0 π π Other   Visits  Health  Center   ACT  at  Drug  Shop   Other   Va(π) Va(π) Vs(π) Vs(π) 0 0 π π Other   ACT    at  Drug  Shop   ACT    at  Drug  Shop   Other   Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 64. Summary: -UT, +OT, T ambiguous Any ACT subsidy will increase rates of ACT access at the drug shop Crowd-out from health care centers ⇒ increases overtreatment Crowd-out from doing nothing ⇒ decreases undertreatment and increases overtreatment If the subsidy policy crowds in enough high-positivity poor relative to low-positivity rich, then overall targeting may improve, but overtreatment will nevertheless increase in any case Whats more: if people are clueless w.r.t their π, then ACT subsidy might crowd-in a lot of low-positivity poor too Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 65. Summary: -UT, +OT, T ambiguous Any ACT subsidy will increase rates of ACT access at the drug shop Crowd-out from health care centers ⇒ increases overtreatment Crowd-out from doing nothing ⇒ decreases undertreatment and increases overtreatment If the subsidy policy crowds in enough high-positivity poor relative to low-positivity rich, then overall targeting may improve, but overtreatment will nevertheless increase in any case Whats more: if people are clueless w.r.t their π, then ACT subsidy might crowd-in a lot of low-positivity poor too Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 66. Summary: -UT, +OT, T ambiguous Any ACT subsidy will increase rates of ACT access at the drug shop Crowd-out from health care centers ⇒ increases overtreatment Crowd-out from doing nothing ⇒ decreases undertreatment and increases overtreatment If the subsidy policy crowds in enough high-positivity poor relative to low-positivity rich, then overall targeting may improve, but overtreatment will nevertheless increase in any case Whats more: if people are clueless w.r.t their π, then ACT subsidy might crowd-in a lot of low-positivity poor too Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 67. Summary: -UT, +OT, T ambiguous Any ACT subsidy will increase rates of ACT access at the drug shop Crowd-out from health care centers ⇒ increases overtreatment Crowd-out from doing nothing ⇒ decreases undertreatment and increases overtreatment If the subsidy policy crowds in enough high-positivity poor relative to low-positivity rich, then overall targeting may improve, but overtreatment will nevertheless increase in any case Whats more: if people are clueless w.r.t their π, then ACT subsidy might crowd-in a lot of low-positivity poor too Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 68. Summary: -UT, +OT, T ambiguous Any ACT subsidy will increase rates of ACT access at the drug shop Crowd-out from health care centers ⇒ increases overtreatment Crowd-out from doing nothing ⇒ decreases undertreatment and increases overtreatment If the subsidy policy crowds in enough high-positivity poor relative to low-positivity rich, then overall targeting may improve, but overtreatment will nevertheless increase in any case Whats more: if people are clueless w.r.t their π, then ACT subsidy might crowd-in a lot of low-positivity poor too Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 69. What if people are clueless? Va(π) Vn(π) Vs(π) Vh(π) π Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 70. How to counteract impact of ACT subsidy onovertreatment? 1. Make subsdized ACT a prescription-only drug: you cant get subsidy if you dont show a positive test result Unfortunately we dont live in a rst-best world... Weak governance / regulatory environment makes this impossible (e.g., see whats happening with free ACTs for malaria+ people at health center) 2. Subsidy for over-the-counter RDT Can get tested before buying ACT ⇒improve targeting But will people take RDTs? Will they adhere to test results? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 71. How to counteract impact of ACT subsidy onovertreatment? 1. Make subsdized ACT a prescription-only drug: you cant get subsidy if you dont show a positive test result Unfortunately we dont live in a rst-best world... Weak governance / regulatory environment makes this impossible (e.g., see whats happening with free ACTs for malaria+ people at health center) 2. Subsidy for over-the-counter RDT Can get tested before buying ACT ⇒improve targeting But will people take RDTs? Will they adhere to test results? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 72. How to counteract impact of ACT subsidy onovertreatment? 1. Make subsdized ACT a prescription-only drug: you cant get subsidy if you dont show a positive test result Unfortunately we dont live in a rst-best world... Weak governance / regulatory environment makes this impossible (e.g., see whats happening with free ACTs for malaria+ people at health center) 2. Subsidy for over-the-counter RDT Can get tested before buying ACT ⇒improve targeting But will people take RDTs? Will they adhere to test results? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 73. How to counteract impact of ACT subsidy onovertreatment? 1. Make subsdized ACT a prescription-only drug: you cant get subsidy if you dont show a positive test result Unfortunately we dont live in a rst-best world... Weak governance / regulatory environment makes this impossible (e.g., see whats happening with free ACTs for malaria+ people at health center) 2. Subsidy for over-the-counter RDT Can get tested before buying ACT ⇒improve targeting But will people take RDTs? Will they adhere to test results? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 74. How to counteract impact of ACT subsidy onovertreatment? 1. Make subsdized ACT a prescription-only drug: you cant get subsidy if you dont show a positive test result Unfortunately we dont live in a rst-best world... Weak governance / regulatory environment makes this impossible (e.g., see whats happening with free ACTs for malaria+ people at health center) 2. Subsidy for over-the-counter RDT Can get tested before buying ACT ⇒improve targeting But will people take RDTs? Will they adhere to test results? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 75. Outline 1. Background: Treatment-Seeking Behavior in Rural Africa 2. Theoretical Framework 3. Experimental Design 4. Results 5. Conclusion Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 76. Experimental Design Catchment Area Census: Target 2,928 Households Households Administered Baseline 2,789 ACT Subsidy ACT+RDT Subsidy No Subsidy 984 1,625 180 Within-Subsidy Price Variation 92% 88% 80% 92% 88% 80% 328 326 330 394 619 612 Endline Follow Up 92% 88% 80% 92% 88% 80% No Subsidy 306 310 317 366 586 587 173 Balance Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 77. Experimental Design Catchment Area Census: Target 2,928 Households Households Administered Baseline 2,789 ACT Subsidy ACT+RDT Subsidy No Subsidy 984 1,625 180 Within-Subsidy Price Variation 92% 88% 80% 92% 88% 80% 328 326 330 394 619 612 Endline Follow Up 92% 88% 80% 92% 88% 80% No Subsidy 306 310 317 366 586 587 173 Balance Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 78. Experimental Design Catchment Area Census: Target 2,928 Households Households Administered Baseline 2,789 ACT Subsidy ACT+RDT Subsidy No Subsidy 984 1,625 180 Within-Subsidy Price Variation 92% 88% 80% 92% 88% 80% 328 326 330 394 619 612 Endline Follow Up 92% 88% 80% 92% 88% 80% No Subsidy 306 310 317 366 586 587 173 Balance Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 79. Sample of 2,911 Illness Episodes Collected roster of illness episodes over 4-month study period at endline (7,733 illnesses) We focus on rst illness episode reported by each household, since we are sure they all had vouchers at that time (2,911 rst illnesses) Diculty: need to know malaria status to assess UT, OT and Targeting Need to know this for everyone, whether they buy ACT or not Idea: Use data on symptoms to predict malaria positivity Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 80. Sample of 2,911 Illness Episodes Collected roster of illness episodes over 4-month study period at endline (7,733 illnesses) We focus on rst illness episode reported by each household, since we are sure they all had vouchers at that time (2,911 rst illnesses) Diculty: need to know malaria status to assess UT, OT and Targeting Need to know this for everyone, whether they buy ACT or not Idea: Use data on symptoms to predict malaria positivity Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 81. Sample of 2,911 Illness Episodes Collected roster of illness episodes over 4-month study period at endline (7,733 illnesses) We focus on rst illness episode reported by each household, since we are sure they all had vouchers at that time (2,911 rst illnesses) Diculty: need to know malaria status to assess UT, OT and Targeting Need to know this for everyone, whether they buy ACT or not Idea: Use data on symptoms to predict malaria positivity Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 82. Sample of 2,911 Illness Episodes Collected roster of illness episodes over 4-month study period at endline (7,733 illnesses) We focus on rst illness episode reported by each household, since we are sure they all had vouchers at that time (2,911 rst illnesses) Diculty: need to know malaria status to assess UT, OT and Targeting Need to know this for everyone, whether they buy ACT or not Idea: Use data on symptoms to predict malaria positivity Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 83. Sample of 2,911 Illness Episodes Collected roster of illness episodes over 4-month study period at endline (7,733 illnesses) We focus on rst illness episode reported by each household, since we are sure they all had vouchers at that time (2,911 rst illnesses) Diculty: need to know malaria status to assess UT, OT and Targeting Need to know this for everyone, whether they buy ACT or not Idea: Use data on symptoms to predict malaria positivity Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 84. Malaria Status of Illness Episodes No clear mapping between symptoms and malaria probability in the medical literature (might be very local anyway) So we had to come up with our own mapping Posted enumerators at drug shop who tested for malaria a random subset of clients (and also recorded their symptoms and age) Use this data to regress malaria status on symptoms and estimate coecient for each symptom, by age group (rst-stage) Use rst-stage coecient estimates and reported symptoms to predict malaria positivity for all illness episodes Predicting Malaria Positivity Wide range of predicted malaria positivity, though higher density at higher probability Distribution of Predicted Malaria Positivity No evidence of reporting bias (those who got ACT subsidy not more likely to report more malaria-looking illnesses) No Reporting Bias Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 85. Outline 1. Background: Treatment-Seeking Behavior in Rural Africa 2. Theoretical Framework 3. Experimental Design 4. Results 5. Conclusion Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 86. Baseline Treatment Seeking by Predicted Positivity First lets check what people are doing at baseline, in the absence of any ACT subsidy or RDT in the retail sector Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 87. Baseline Treatment Seeking by Predicted Positivity A. All B. Literate Head C. Illiterate Head 1 1 1 .8 .8 .8 .6 .6 .6 Share Share Share .4 .4 .4 .2 .2 .2 0 0 0 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Predicted Positivity Predicted Positivity Predicted Positivity ACT at Drug Shop Visit to Health Center Other Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 88. Baseline Treatment Seeking by Predicted Positivity Figure 5. Baseline Malaria Treatment Seeking Behavior by Predicted Positivity and Literacy of Household Head A. All B. Literate Head C. Illiterate Head 1 1 1 .8 .8 .8 .6 .6 .6 Share Share Share .4 .4 .4 .2 .2 .2 0 0 0 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Predicted Positivity Predicted Positivity Predicted Positivity ACT at Drug Shop Visit to Health Center Other Notes: Data from No Subsidy group. Local linear regression lines trimmed at 2.5 percent. Tertiles demarcated by gray vertical lines. Median demarcated by dashed gray vertical line. Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 89. Impact of Proposed ACT Subsidy 1. Impact on where people went for treatment 2. Impact on ACT treatment rate Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 90. Treatment-Seeking at Drug Shop Increases Figure 6. Impact of Retail Sector ACT Subsidy on Provider Choice Where was Care Sought? Drug Shop Health Center No Care .5 .6 1 .8 .4 lpoly smooth: J5: went to chemist .6 .4 .8 .3 Share Share Share .4 .2 .2 .6 .2 .1 0 0 0 .4 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Predicted Positivity Predicted Positivity Predicted Positivity 0 .2 .4 .6 .8 1 No Subsidy ACT Subsidy Notes: Local linear regression lines trimmed at 2.5 percent. Gray vertical lines demarcate tertiles. Dashed gray vertical line shows median. Excludes households randomly selected for surprise RDT testing at drug shop. Crowding out of health center at higher malaria probability Crowding out of no care at low malaria probability Cohen, Dupas, Schaner 47 Subsidies and Malaria Treatment IFPRI, August 2012
  • 91. Crowd-in concentrated among Richer HHs Literate Drug Shop Health Center No Care .5 .6 .8 .4 .6 .4 .3 Share Share Share .4 .2 .2 .2 .1 0 0 0 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Predicted Positivity Predicted Positivity Predicted Positivity Illiterate Drug Shop Health Center No Care .5 .6 .8 .4 .6 .4 .3 Share Share Share .4 .2 .2 .2 .1 0 0 0 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Predicted Positivity Predicted Positivity Predicted Positivity No Subsidy ACT Subsidy Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 92. Impact of Proposed ACT Subsidy 1. Impact on where people went for treatment 2. Impact on ACT treatment rate Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 93. Large increase in ACT Access Figure 7. Impact of Retail Sector ACT Subsidy on ACT Access Illness was Treated with ACT 1 A. All B. Literate Head C. Illiterate Headlpoly smooth: J5: went to chemist .6 .6 .6 .8 Share Share Share .4 .4 .4 .6 .2 .2 .2 0 0 0 .4 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Predicted Positivity Predicted Positivity Predicted Positivity 0 .2 .4 .6 .8 1 No Subsidy ACT Subsidy Notes: Local linear regression lines trimmed at 2.5 percent. Gray vertical lines demarcate tertiles. Dashed gray vertical line shows median. Excludes households randomly selected for surprise RDT testing at drug shop. Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 94. Type I Errors mostly among AdultsResults from Surprise Malaria Tests among subsidized ACT buyers at Drug Shops 86 percent of patients ≤ 13 are malaria positive, 44 percent of patients 13 are positive Figure 1. Actual and Predicted Malaria Positivity by Age .8 Share Malaria Positive .2 .4 0 .6 0 20 40 60 80 Age Test Result - All Patients with Symptoms Test Result - Patients Taking ACT Predicted Positivity - Patients Taking ACT Notes: Local linear regression results for patients aged 80 and younger. Test Result is a 0/1 malaria status variable that comes from rapid malaria diagnostic Still, some advantageous selection onto ACT taking on unobservables tests administered by trained enumerators to patients visited at home within 3 days of the start of the illness (grey line), or to patients for whom and ACT was purchased at the drug shop (solid black line). Cohen, Dupas, Predicted Positivity Subsidies and Malaria Treatment Schaner is a variable between 0 and 1 that is imputed based on reported IFPRI, August 2012
  • 95. Type I Errors mostly among AdultsResults from Surprise Malaria Tests among subsidized ACT buyers at Drug Shops 86 percent of patients ≤ 13 are malaria positive, 44 percent of patients 13 are positive Figure 1. Actual and Predicted Malaria Positivity by Age .8 Share Malaria Positive .2 .4 0 .6 0 20 40 60 80 Age Test Result - All Patients with Symptoms Test Result - Patients Taking ACT Predicted Positivity - Patients Taking ACT Notes: Local linear regression results for patients aged 80 and younger. Test Result is a 0/1 malaria status variable that comes from rapid malaria diagnostic Still, some advantageous selection onto ACT taking on unobservables tests administered by trained enumerators to patients visited at home within 3 days of the start of the illness (grey line), or to patients for whom and ACT was purchased at the drug shop (solid black line). Cohen, Dupas, Predicted Positivity Subsidies and Malaria Treatment Schaner is a variable between 0 and 1 that is imputed based on reported IFPRI, August 2012
  • 96. Preferred Subsidy SchemeHow big does the ACT subsidy have to be? Its clear that an ACT subsidy through retail sector is needed since access is very low without it (esp. among low SES) But its also clear that willingness-to-pay for malaria treatment is not low (we observe large expenses per episode at baseline) Could the ACT subsidy be a bit smaller than planned (say 80% instead of 95%)? Would that help deter overtreatment without reducing access (compared to proposed subsidy)? Alternatively, introduce RDT subsidy? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 97. Preferred Subsidy SchemeHow big does the ACT subsidy have to be? Its clear that an ACT subsidy through retail sector is needed since access is very low without it (esp. among low SES) But its also clear that willingness-to-pay for malaria treatment is not low (we observe large expenses per episode at baseline) Could the ACT subsidy be a bit smaller than planned (say 80% instead of 95%)? Would that help deter overtreatment without reducing access (compared to proposed subsidy)? Alternatively, introduce RDT subsidy? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 98. Preferred Subsidy SchemeHow big does the ACT subsidy have to be? Its clear that an ACT subsidy through retail sector is needed since access is very low without it (esp. among low SES) But its also clear that willingness-to-pay for malaria treatment is not low (we observe large expenses per episode at baseline) Could the ACT subsidy be a bit smaller than planned (say 80% instead of 95%)? Would that help deter overtreatment without reducing access (compared to proposed subsidy)? Alternatively, introduce RDT subsidy? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 99. Preferred Subsidy SchemeHow big does the ACT subsidy have to be? Its clear that an ACT subsidy through retail sector is needed since access is very low without it (esp. among low SES) But its also clear that willingness-to-pay for malaria treatment is not low (we observe large expenses per episode at baseline) Could the ACT subsidy be a bit smaller than planned (say 80% instead of 95%)? Would that help deter overtreatment without reducing access (compared to proposed subsidy)? Alternatively, introduce RDT subsidy? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 100. Which Subsidy Regime? Preview... Illness was Treated with ACT .6 .6 .6 .5 .5 .5 Share Share Share .4 .4 .4 .3 .3 .3 .2 .2 .2 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Predicted Positivity Predicted Positivity Predicted Positivity ACT 80% Subsidy ACT 92%+RDT Subsidy ACT 80% + RDT Subsidy ACT 92% Subsidy ACT 92% Subsidy ACT 92% Subsidy No Subsidy No Subsidy No Subsidy Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 101. Price Sensitivity within ACT Subsidy Group .6 .4 .2 0 Used ACT Voucher 92%88% 80% 0% Subsidy Level Literate Head Illiterate Head Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 102. Targeting Results Does higher price crowd-out those less likely to have malaria? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 103. Targeting Results Share Malaria Positive .9 .8 .7 .6 .5 92% 88% 80% Subsidy Level Mean 95% CI Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 104. Higher ACT Price Crowds-out Adults Table 4. Impact of Variation in ACT Subsidy Level on ACT Access and Targeting (1) (2) (3) (4) (5) Panel A. Retail-Sector ACTs First ACT Voucher Predicted Malaria Redeemed First Redeemed First was Redeemed for Positivity of Patient Redeemed ACT Voucher ACT Voucher Malaria Positive for Whom First ACT First ACT for Child (Ages for Adult (Ages Patient Voucher was Voucher 13 and Below) 14 and Above) (RDT Result) Redeemed ACT Subsidy = 88% -0.027 0.032 -0.058** 0.187** 0.112*** (0.038) (0.034) (0.027) (0.080) (0.042) ACT Subsidy = 80% -0.055 0.027 -0.082*** 0.182** 0.107*** (0.037) (0.034) (0.026) (0.084) (0.043) P-value: 88%=80%=0 0.338 0.603 0.006*** 0.036** 0.011** DV Mean (ACT 92%, no RDT) 0.439 0.268 0.171 0.563 0.424 N 2609 2609 2609 687 685 Panel B. Overall ACT Access If Child If Adult (Ages 13 and (Ages 14 and If Illness was Treated Below): Above): With ACT: Ilness Treated Illness Treated Illness Treated Predicted Malaria With ACT With ACT With ACT Positivity ACT Subsidy = 88% -0.042 0.001 -0.128 0.090* (0.060) (0.081) (0.087) (0.051) ACT Subsidy = 80% -0.017 0.021 -0.091 0.042 (0.058) (0.080) (0.083) (0.051) P-value: 88%=80%=0 0.783 0.951 0.323 0.213 DV Mean (ACT 92%, no RDT) 0.457 0.462 0.450 0.431 N 1880 1085 794 816 Notes: Panel A: The unit of observation is the household. Panel B: The unit of observation is the first illness episode that the household experienced following the baseline. Subsidiescutoff Malaria Treatment adult dosage is recommendedAugust 2012 Cohen, Dupas, Schaner 14 is the and age above which the IFPRI, (see Figure
  • 105. Preferred Subsidy Scheme? An 80% ACT subsidy gets almost the same reduction in undertreatment as 95% subsidy, but leads to lower overtreatment rate Still, about 50% of adult ACT takers at that price are malaria negative Suggests need for diagnostic testing Next we look at impact of RDT subsidy Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 106. Preferred Subsidy Scheme? An 80% ACT subsidy gets almost the same reduction in undertreatment as 95% subsidy, but leads to lower overtreatment rate Still, about 50% of adult ACT takers at that price are malaria negative Suggests need for diagnostic testing Next we look at impact of RDT subsidy Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 107. Preferred Subsidy Scheme? An 80% ACT subsidy gets almost the same reduction in undertreatment as 95% subsidy, but leads to lower overtreatment rate Still, about 50% of adult ACT takers at that price are malaria negative Suggests need for diagnostic testing Next we look at impact of RDT subsidy Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 108. Preferred Subsidy Scheme? An 80% ACT subsidy gets almost the same reduction in undertreatment as 95% subsidy, but leads to lower overtreatment rate Still, about 50% of adult ACT takers at that price are malaria negative Suggests need for diagnostic testing Next we look at impact of RDT subsidy Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 109. Only modest impact of RDT on Targeting Share Malaria Positive .9 .8 .7 .6 .5 92% 88% 80% Subsidy Level No RDT RDT Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 110. Even though people are willing to experiment with RDTs Figure 8. Impact of Retail Sector RDT Subsidy on Malaria Testing Took Malaria Test A. All B. Literate Head C. Illiterate Head 1 .6 .6 .6 lpoly smooth: J5: went to chemist .8 .4 .4 .4 Share Share Share .6 .2 .2 .2 .4 0 0 0 .2 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Predicted Positivity Predicted Positivity Predicted Positivity 0 .2 .4 .6 .8 1 ACT Subsidy Only ACT + RDT Subsidy Notes: Local linear regression lines trimmed at 2.5 percent. Gray vertical lines demarcate tertiles. Dashed gray vertical line shows median. Excludes households without RDT vouchers that were randomly selected for surprise RDT testing at drug shop. Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 111. Problem: Compliance with RDT results is imperfect 46 percent of individuals aged 9 and older took an ACT when they tested negative Not surprising? Rural microscopy very unreliable (Batwala et al 2010) Could RDTs become more eective in the long run? Even if compliance is not perfect, benets to getting test: 1. More likely to seek alternative diagnosis 2. Less likely to negatively update about ACT if health does not improve after taking it Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 112. Which Subsidy Regime? ReviewTable 5. Estimated Impacts of Various Subsidy Schemes on Under- and Over-Treatment No ACT 92% ACT 80% ACT 80% + Subsidy Subsidy Subsidy RDT Subsidy Total Share Taking ACT A 0.282 0.457 0.437 0.432Experimental Estimates of Access and Drug Shop Targeting (from Table 4) Share Taking ACT at Drug Shop S 0.170 0.355 0.334 0.338 Share Taking ACT at Health Center 1-S 0.113 0.101 0.104 0.094 Targeting at Drug Shop TS 0.745 0.563 0.745 0.806 Share of illness episodes that are malaria a Π 0.386 0.386 0.386 0.386Assumptions for Estimates of Under- and Over-Treatment Targeting at Health Center (Medium) b TH1 0.75 0.75 0.75 0.75 Overall Targeting T1 = [S x Ts + (1 - S) x TH1 ]/A 0.747 0.605 0.747 0.794Under- and Over-Treatment: Preferred Estimates (assuming Medium Targeting at Health Center) Over Treatment OT1 = S x (1 - T1) / Π 0.116 0.294 0.181 0.145 Under Treatment UT1 = (1 - S) x T1 / Π 0.453 0.284 0.153 0.110Notes: Targeting (T) is the share of ACTs taken for illness episodes that are malaria.Overtreatment (OT) is the share of non-malaria episodes treated with an ACT.Undertreatment (UT) is the share of malaria episodes not treated with an ACT.a The assumption on the share of illness episodes that are malaria (Π) is based on the rate observeed in the symptoms database collectedthrough unannounced household visits during which rapid diagnostic tests for malaria were administered. See text for details.b We consider three possible levels of targeting at health centers since there is no clear evidence from the literature on this parameter. Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 113. External Validity Table 6. External Validity Comparisons Western and Central Eastern Southeastern Southern Uganda Uganda Tanzania Malawi November- December May-June January- 2010 2011 March 2011 March 2011 HH Had at least one (Presumed) Malaria Malaria Burden (reported/perceived) Episode (Past Month) 0.590 0.354 0.273 0.410 Public Sector 0.250 0.333 0.417 0.760 Treatment Seeking for Malaria Private Sector* 0.660 0.426 0.392 0.120 No Treatment Sought 0.090 0.221 0.187 0.120 Last Month 0.150 0.225 Malaria Diagnosis (Any Blood Malaria Test) Last Suspected Episode 0.360 Took ACT (Suspected Malaria) 0.330 0.376 0.496 Medication Taken Antimalarial Cost 1.690 1.355 1.366 Under 5 0.740 Malaria Positivity Among Drug Shop Patients Buying Subsidized ACTs Ages 5 - 13 0.780 Ages 14 and Up 0.470 Under 5 0.512 Malaria Positivity Among The General Population Ages 5 - 13 0.644 Ages 14 and Up 0.351 *Includes private clinics and retail sector a Survey conducted in Luwero district. Malaria positivity figures are among purchasers of subsidized ACTs Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 114. Outline 1. Background: Treatment-Seeking Behavior in Rural Africa 2. Theoretical Framework 3. Experimental Design 4. Results 5. Conclusion Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 115. Conclusion Subsidizing ACTs increases ACT access by nearly 50 percent Good news large increases at high predicted probabilities, largely crowding out less eective medicine Bad news large increases at low predicted probabilities wasted subsidy money, drug resistance development Crucial need for better access to reliable diagnostic testing Ideally: make accessibility conditional on positive test result Diverting part of the ACT subsidy towards an RDT subsidy may be a cost-eective move But RDTs are no immediate panacea Our sample was very willing to experiment with RDTs, but adherence was incomplete. Also, RDTs do not draw people to the drug shop. Are people just learning about a new technology? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 116. Conclusion Subsidizing ACTs increases ACT access by nearly 50 percent Good news large increases at high predicted probabilities, largely crowding out less eective medicine Bad news large increases at low predicted probabilities wasted subsidy money, drug resistance development Crucial need for better access to reliable diagnostic testing Ideally: make accessibility conditional on positive test result Diverting part of the ACT subsidy towards an RDT subsidy may be a cost-eective move But RDTs are no immediate panacea Our sample was very willing to experiment with RDTs, but adherence was incomplete. Also, RDTs do not draw people to the drug shop. Are people just learning about a new technology? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 117. Conclusion Subsidizing ACTs increases ACT access by nearly 50 percent Good news large increases at high predicted probabilities, largely crowding out less eective medicine Bad news large increases at low predicted probabilities wasted subsidy money, drug resistance development Crucial need for better access to reliable diagnostic testing Ideally: make accessibility conditional on positive test result Diverting part of the ACT subsidy towards an RDT subsidy may be a cost-eective move But RDTs are no immediate panacea Our sample was very willing to experiment with RDTs, but adherence was incomplete. Also, RDTs do not draw people to the drug shop. Are people just learning about a new technology? Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 118. APPENDIX SLIDESCohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 119. Predicting Malaria Positivity Appendix Table A3. Predicting Malaria Positivity - Probit Marginal Effects Coefficient Standard Error Cough -0.001 (0.061) Chills 0.132 (0.097) Headache 0.125* (0.072) Diarrhea 0.247*** (0.084) Runny Nose -0.119** (0.060) Vomiting 0.063 (0.072) Body Pain 0.197* (0.111) Malaise -0.052 (0.149) Poor Appetite 0.131 (0.104) Age 14 or Above 0.398* (0.239) Age 0.106*** (0.032) Age Squared -0.008*** (0.003) (Age 14 or Above)×Cough -0.096 (0.126) (Age 14 or Above)×Chills -0.235** (0.113) (Age 14 or Above)×Headache -0.070 (0.126) (Age 14 or Above)×Diarrhea -0.221* (0.131) (Age 14 or Above)×Runny Nose 0.222 (0.147) (Age 14 or Above)×Vomiting 0.089 (0.155) (Age 14 or Above)×Body Pain -0.106 (0.133) (Age 14 or Above)×Malaise -0.075 (0.171) (Age 14 or Above)×Poor Appetite 0.005 (0.260) (Age 14 or Above)×Age -0.138*** (0.034) (Age 14 or Above)×Age Squared 0.009*** (0.003) DV Mean / N 0.003 1386 Notes: Standard errors in parentheses. Data source: Symptoms database (see text sections 4.3 and 4.4 for details). ***, **, and * indicate significance at the 99, 95, and Back 90 percent levels respectively. We do not include the most commonly cited symptom Cohen, Dupas, of malaria, fever, in order to avoidand Malaria Treatment Kiswahili, the word for Schaner Subsidies endline reporting bias. In IFPRI, August 2012
  • 120. Predicted Malaria Positivity Among Illness EpisodesEnumerated at Endline All 2 1.5 Density 1.5 0 0 .2 .4 .6 .8 1 Predicted Malaria Prositivity Back Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 121. Predicted Malaria Positivity Among Illness EpisodesEnumerated at Endline Adults 4 3 Density 21 0 0 .2 .4 .6 .8 1 Predicted Malaria Prositivity Back Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 122. No Signicant Reporting Bias Among Endline IllnessEpisodes Reported # Episodes Predicted Episode Patient Episode Reported Positivity Days Ago Age ACT Subsidy -0.00246 -0.0767 0.0295 3.24 -2.10 (0.0198) (0.147) (0.0207) (3.58) (1.54) ACT × RDT Subsidy 0.00340 -0.0414 -0.00170 -1.02 0.839 (0.00967) (0.0768) (0.0102) (1.85) (0.765) Surprise RDT 0.00387 0.103 -0.0125 5.00*** 0.994 (0.0103) (0.0780) (0.0105) (1.93) (0.796) DV Mean .95 3.05 .626 64.7 19.1 N 2621 2621 2473 2438 2473 ***, **, and * indicate signicance at the 99, 95, and 90 percent levels. Back Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 123. Randomization Verication - I Variable Means P-values Control ACT +RDT C=T1 C=T2 T1=T2 N Characteristics of Interviewed Household Head Female 0.867 0.895 0.907 0.292 0.125 0.333 2789 Age (years) 41.7 38.8 38.8 0.041** 0.036** 0.981 2646 Education (years) 5.10 5.36 5.54 0.424 0.158 0.253 2774 Literate 0.575 0.621 0.621 0.258 0.236 0.973 2782 Married 0.783 0.789 0.777 0.860 0.841 0.456 2784 Num. dependents 4.12 4.07 4.13 0.822 0.979 0.586 2663 Household Characteristics Number members 5.48 5.29 5.34 0.382 0.521 0.585 2789 Acres land 2.72 2.08 2.28 0.045** 0.175 0.0870* 2250 Drug shop dist. (km) 1.68 1.66 1.67 0.873 0.966 0.809 2788 ***, **, and * indicate signicance at the 99, 95, and 90 percent levels. Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 124. Randomization Verication - II Variable Means P-values Control ACT +RDT C=T1 C=T2 T1=T2 N Baseline Malaria Knowledge and Health Practices Number bednets 1.77 1.77 1.78 0.994 0.929 0.875 2784 Share slept under net 0.561 0.585 0.573 0.450 0.698 0.455 2661 Heard of ACTs 0.399 0.425 0.427 0.519 0.467 0.904 2771 Heard of RDTs 0.128 0.153 0.140 0.365 0.646 0.375 2786 Treats water regularly 0.408 0.390 0.416 0.648 0.841 0.190 2779 Malaria eps. last month 1.20 1.20 1.23 0.985 0.744 0.508 2789 Cost Per Episode (Among Those Seeking Any care) Total Cost (Ksh) 127 120 131 0.694 0.825 0.405 1319 ***, **, and * indicate signicance at the 99, 95, and 90 percent levels. Back Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 125. Empirical SpecicationsStart with roster of all illness episodes at endline Limit to rst episode (all treatment households will have ACT and/or RDT vouchers)For outcome yeh (episode e in household h) 1. Local linear regression on predicted positivity by treatment group yeh = g (poseh ) + eh 2. Regressions to estimate average impacts of each treatment yeh = δ + αactsubh + βactrdtsubh + γage + λstrata + ε eh 3. Examine average impacts by tertile of predicted malaria positivity 3 yeh = δ+ ∑ (αt actsubh × tertileth + βt actrdtsubh × tertileth ) t =1 +γage + λstrata + ε eh Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 126. Empirical SpecicationsStart with roster of all illness episodes at endline Limit to rst episode (all treatment households will have ACT and/or RDT vouchers)For outcome yeh (episode e in household h) 1. Local linear regression on predicted positivity by treatment group yeh = g (poseh ) + eh 2. Regressions to estimate average impacts of each treatment yeh = δ + αactsubh + βactrdtsubh + γage + λstrata + ε eh 3. Examine average impacts by tertile of predicted malaria positivity 3 yeh = δ+ ∑ (αt actsubh × tertileth + βt actrdtsubh × tertileth ) t =1 +γage + λstrata + ε eh Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 127. Empirical SpecicationsStart with roster of all illness episodes at endline Limit to rst episode (all treatment households will have ACT and/or RDT vouchers)For outcome yeh (episode e in household h) 1. Local linear regression on predicted positivity by treatment group yeh = g (poseh ) + eh 2. Regressions to estimate average impacts of each treatment yeh = δ + αactsubh + βactrdtsubh + γage + λstrata + ε eh 3. Examine average impacts by tertile of predicted malaria positivity 3 yeh = δ+ ∑ (αt actsubh × tertileth + βt actrdtsubh × tertileth ) t =1 +γage + λstrata + ε eh Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 128. Empirical SpecicationsStart with roster of all illness episodes at endline Limit to rst episode (all treatment households will have ACT and/or RDT vouchers)For outcome yeh (episode e in household h) 1. Local linear regression on predicted positivity by treatment group yeh = g (poseh ) + eh 2. Regressions to estimate average impacts of each treatment yeh = δ + αactsubh + βactrdtsubh + γage + λstrata + ε eh 3. Examine average impacts by tertile of predicted malaria positivity 3 yeh = δ+ ∑ (αt actsubh × tertileth + βt actrdtsubh × tertileth ) t =1 +γage + λstrata + ε eh Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 129. Typical Drug Shops (Chemists)       Back Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012
  • 130. USA Kenya Malawi MaliPhysicians (per 1,000 people) 2.7 0.14 0.02 0.08 Nurses (per 1,000 people) 8.8 1 1 1Source: World Develpment indicators (WDI) (2004)Back Cohen, Dupas, Schaner Subsidies and Malaria Treatment IFPRI, August 2012

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