The Global Enteric Multi-Center Study (GEMS): Etiology & Burden of Moderate & Severe Diarrheal Disease in Africa & Asia

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The Global Enteric Multi-Center Study (GEMS): Etiology & Burden of Moderate & Severe Diarrheal Disease in Africa & Asia

  1. 1. The Global Enteric Multi-Center Study(GEMS): Etiology & Burden of Moderate & Severe Diarrheal Disease in Africa & Asia Myron M (Mike) Levine, MD, DTPH Grollman Distinguished Professor & Director Center for Vaccine Development, University of Maryland School of Medicine Baltimore, MD 21201, USA PAS Annual Meeting, April 30, 2012 CVD Boston, MA, USA
  2. 2. UN Millenium Development Goal # 4 aims to diminishmortality in children < 5 years of age by 67% by 2015Of the 35 countries with thehighest under-five mortality,34 are in sub-Saharan Africa!!!(State of the World’s Children, UNICEF 2011)
  3. 3. Deaths amongchildren < 5years of age (CHERG data)RE Black et al, Lancet 2010 CVD
  4. 4. Clinical syndromes“Simple” gastroenteritis Watery diarrhea, mucus, some vomiting, low-grade fever, malaise, anorexia; dehydration in infants Profuse watery diarrhea Purging of voluminous rice water stools; dehydration of older children & adultsDysentery Blood & mucus in diarrheal stoolsPersistent diarrhea CVD Continues > 14 days, unabated
  5. 5. Some limitations of earlier studies• Few studies from countries with high child mortality• Very few studies from sub-Saharan Africa• Typically only one site studied per report• Often limited to children < 24 months of age• Most had short surveillance (only 6-24 calendar months; too limited to detect cyclical patterns)• Failure to enroll and study matched controls• Lack of census data or linkage to a DSS• Health care utilization patterns not known• Incomplete survey of etiological agents• Insensitive microbiological methods• Strains not characterized for serotype, genotype, etc.• No follow-up of cases & controls
  6. 6. GLOBAL ENTERIC MULTI-CENTER STUDY (“GEMS”) Diarrheal disease in infants & young children in developing countries Project Funded by Bill & Melinda Gates Foundation The GEMS Leadership Team: Coordinating Investigator Myron M. (Mike) Levine, M.D., D.T.P.H. Center for Vaccine Development, University of Maryland School of Medicine Principal Investigator, epidemiology & clinical Karen L. Kotloff, M.D.CVD Principal Investigator, microbiology James P. Nataro, M.D., Ph.D. (since 9/2010, Professor & Chair, Dept. of Pediatrics, U. of Virginia)
  7. 7. • Common protocol to study moderate & severe diarrhea (MSD)• Rigorous epidemiologic case/control & microbiologic design• Defined population under demographic surveillance• 3 age strata: 0-11 mos; 12-23 mos; 24-59 mos• Health Services Utilization & Attitudes Survey (HUAS); 1000/site• 600 analyzable cases & > 600 analyzable matched controls per age group, per each of 7 sites, over 3 years• Record all diarrhea and all MSD cases coming to sentinel sites• Even sampling throughout the year (8-9 cases per age stratum, per fortnight, throughout the enrollment period)• AFRICA & ASIA; rural & urban; high & low HIV; high & low malaria• Record specific clinical syndromes• Utilize modern molecular diagnostic tools• Expanded etiology; serotypes; antigenic types; genotypes• 60-DAY FOLLOW-UP VISITS of cases & controls – Detect deaths; nutritional consequences; (persistent diarrhea)• Water/sanitation risk factor data & economic burden data• SPECIMEN & STRAIN REPOSITORY
  8. 8. 4 GEMS Sites in Sub-Saharan AfricaCDC/KEMRI, Kisumu, Kenya PI – Robert BreimanMRC Unit, Basse, Gambia PI – Debasish Saha Richard Adegbola Jahangir HusseinCISM, Manhiça, Mozambique PI – Pedro AlonsoCVD-Mali, Bamako, Mali PI – Samba Sow3 GEMS Sites in South AsiaAga Khan University, Pakistan PI – Anita ZaidiNICED, Kolkata, West Bengal, India PI- Dipika SurICDDR,B: Mirzapur, Bangladesh PI- ASG Faruque
  9. 9. Salient features of the seven GEMS-1 sites Manhiça, Mirzapur, Basse, Bamako, Kisumu, Karachi, Kolkata,Site Mozam- Bangla- Gambia Mali Kenya Pakistan India bique desh Coastal Mostly MostlySetting Very rural Urban Rural fishing Urban rural rural villagesNational 67.5 113.7 103.8 53.5 52.5 65.3 49.1IMR*DSSannual 157,726 210,425 84,206 141,628 254,751 252,346 194,172pop’n (28,898) (32,526) (16,657) (23,294) (24,077) (24,792) (12,885)(< 5 yrs)Malariapreva- Moderate Moderate Moderate Mod- Low Low Lowlence (falling) (falling) erateHIVpreva- Low Low High High Low Low Lowlence* IMR, infant mortality rate = deaths of infants 0-11 months of age per 1000 live births
  10. 10. Some GEMS assumptions• A limited number of etiologic agents may be responsible for a disproportionately large fraction of MSD• MSD seen at SHCs is a proxy for fatal disease in the community• The appropriate epidemiologic design for identifying the relative importance of pathogens associated with MSD is a matched case/control study (MSD uncommon)• We can standardize clinical and lab methods across sites and maintain GCP, GCLP and Quality Control• Making a single 60-day post-enrollment visit to case & control households creates prospective mini-cohorts• Results will facilitate the setting of investment & intervention priorities
  11. 11. Study AdvisoriesSteering Committee on Epidemiology/Clinical Issues Fred Binka (Ghana), Eric Mintz (CDC), Paul Stolley (UM), John Clemens (IVI), Halvor Sommerfelt (Bergen), Dani Cohen (Tel Aviv U), Roger Glass (Fogarty)Steering Committee on Microbiologic Issues Roy Robins-Browne (U of Melbourne), Philippe Sansonetti (Institut Pasteur), Patrick Murray (NIH), Duncan Steele (PATH)Steering Committee on Biostatistical Issues Larry Moulton (JHU), Barry Graubard (NCI), Peter Smith (LSTMH), Janet Wittes (Statistics Collaborative), William Pan (Duke)Steering on Nutritional IssuesReynaldo Martorell (Emory), Claudio Lanata (IIN), Rebecca Stoltzfus (Cornell)Consensus -- Case/control protocol & microbiologic methods & analytical strategies were finalized after consultations with the SCsReference Laboratories
  12. 12. MSD case eligibility & enrollment • Age 0-59 mos. & from DSS • Seeking care at a sentinel Health Center (SHC) • Diarrhea (> 3 loose stools in previous 24h) • Diarrhea-free for 7 days before current episode • Episode began within 7 days of enrollment • Diarrhea is moderate or severe, i.e., has > 1 of: – Moderate/severe dehydration: • Sunken eyes • Loss of skin turgor • IV rehydration requiredCVD – Dysentery (gross blood & mucus) – Hospitalized (clinician’s judgment)
  13. 13. Selection of controls• Community controls randomly selected using DSS database• 1-3 controls/case• Matched to case by: – Age (strata are respected) • 0-11 mos: +2 months • 12-59 mos: +4 months – Gender – Same or nearby village – Within 14 days of presentation of case• No diarrhea within 7 days of enrollment• Provides stool sample of acceptable quality• Informed consent
  14. 14. Microbiology work flowCVD
  15. 15. Full 36 mos. of ALL SITES GEMS data Controls enrolled Controls enrolled 13,125 6810 6315 A AS Cases enrolled 9524 Cases enrolledRIC 5282 (65%) 4242 IA MSD eligibles 14,753 MSD eligiblesAF 9149 (21%) 5604 All cases of diarrhea All cases of diarrhea seen at SHCs 71,364 seen at SHCs 35,984 35,380 CYO < 60 mos in DSS CYO < 60 mos in DSS 483,627 295,164 188,463
  16. 16. Pathogens (including Giardia) identified in stoolspecimens from cases and controls during the first 2 years of GEMSNo. of 4 African sites 3 Asian sitespathogensidentified Cases (%) Ctrls (%) Cases (%) Ctrls (%)At least 1 79 71 83 70At least 2 37 29 47 32At least 3 10 7 16 10
  17. 17. Pathogen isolations, India site, 12-23 months age group. 588 cases & 598 controls (3-year data)Pathogen Cases Pathogen CasesRotavirus 151 Astrovirus 19Giardia 138 tEPEC 18Cryptosporidium 98 ETEC - LT only 17Campylobacter jejuni 83 E. histolytica 14EAEC 72 Adenovirus non-40-41 11Norovirus GII 51 Campylobacter coli 5Shigella 40 Norovirus GI 4Adenovirus 40/41 29 Aeromonas 2ST-only ETEC 26 EHEC 2Sapovirus 24 Non-typhoidal Salmonella 1V. cholerae O1 21ETEC - LT/ST 21aEPEC 21
  18. 18. Pathogen isolations, India site, 12-23 months age group. 588 cases & 598 controls (3-year data)Pathogen Cases Ctrls Pathogen Cases CtrlsRotavirus 151 13 Astrovirus 19 13Giardia 138 173 tEPEC 18 18Cryptosporidium 98 60 ETEC - LT only 17 21Campylobacter jejuni 83 76 E. histolytica 14 4EAEC 72 82 Adenovirus non-40-41 11 11Norovirus GII 51 33 Campylobacter coli 5 9Shigella 40 7 Norovirus GI 4 12Adenovirus 40/41 29 4 Aeromonas 2 5ETEC - ST-only 26 9 EHEC 2 0Sapovirus 24 15 Non-typhoidal Salmonella 1 2V. cholerae O1 21 2ETEC - LT/ST 21 6aEPEC 21 66
  19. 19. Attributable Fraction (AF) Grappling with the issue of enteric pathogens in matched controls without diarrhea • Fraction of all MSD (moderate & severe diarrhea) cases attributable to (presumably caused by) a particular pathogen • Fraction of MSD cases or MSD incidence rate that could theoretically be eliminated if the pathogen were eliminated Grappling with the issue of multiple enteric pathogens in cases & controls • Bruzzi et al (AJE 1985) allows AF to be calculated whileCVD taking into account the presence of other pathogens • Allows AF for a group of pathogens (e.g., “Top 5”)
  20. 20. India, age 12-23 months: 588 cases, 598 controls (3 years of data) Cases Ctrls Adj With With Adj AttribPathogen Pathogen Pathogen OR p-value AF CasesRotavirus 151 13 21.1 <0.0001 0.278 144Cryptosporidium 98 60 2.1 0.002 0.088 52Shigella 40 7 14.6 <0.0001 0.063 37LT/ST or ST-only 47 15 3.8 <0.0001 0.059 35Adenovirus 40/41 29 4 11.1 <0.0001 0.045 26V. cholerae O1 21 2 10.4 0.001 0.032 19E. histolytica 14 4 5.4 0.045 0.019 11
  21. 21. Pathogen-specific adjusted attributable fractions, 0-11 months age group, “Top 5” analysis (3 yrs of data) 0-11 m Gambia Kenya Mali Mozam India Bangla PakistanTotal cases 400 673 727 374 672 550 633#1 RV RV RV RV RV RV RV (23%) (19%) (21%) (32%) (28%) (17%) (23%)#2 Crypto Crypto Crypto Crypto Crypto Shigella Aeromon (11%) (9%) (14%) (14%) (13%) (13%) (11%)#3 Noro-GII ETEC ST or ETEC ST or ETEC ST or Adeno C. jejuni ETEC ST or (7%) LT/ST (6%) LT/ST (4%) LT/ST (3%) 40/41 (4%) (10%) LT/ST (7%)#4 ETEC ST or tEPEC Adeno Adeno ETEC ST or Aeromo Shigella LT/ST (4%) (5%) 40/41 (2%) 40/41 (2%) LT/ST (3%) (10%) (7%)#5 Shigella Shigella Shigella Crypto Crypto (4%) (4%) (2%) (6%) (4%)“Top 5” - %of all cases 47% 40% 38% 47% 46% 49% 46%
  22. 22. Pathogen-specific adjusted attributable fractions 12-23 months age group, “Top 5”analysis (3 yrs of data) 12-23 m Gambia Kenya Mali Mozam India Bangla PakistanTotal cases 455 410 682 194 588 476 399 #1 RV RV RV Crypto RV Shigella Shigella (17%) (14%) (12%) (9%) (24%) (53%) (11%) #2 Shigella Crypto Crypto ETEC ST or Crypto RV Aeromon (12%) (8%) (4%) LT/ST (9%) (9%) (17%) (11%) #3 Noro-GII ETEC ST or ETEC ST or Shigella Shigella Aeromon RV (8%) LT/ST (7%) LT/ST (3%) (6%) (6%) (11%) (10%) #4 Crypto Shigella Shigella RV ETEC ST or EAEC Crypto (8%) (4%) (2%) (5%) LT/ST (6%) (9%) (8%) #5 ETEC ST or NTS - C. jejuni Noro-GII V. chol V. chol LT/ST (6%) (4%) (2%) (5%) O1 (1%) O1 (8%)“Top 5” - % all cases 45% 34% 20% 36% 45% 76% 47%
  23. 23. Pathogen-specific adjusted attributable fractions 24-59 months age group. “Top 5” analysis (3 yrs of data) 24-59 m Gambia Kenya Mali Mozam India Bangla PakistanTotal cases 174 393 624 112 308 368 226 #1 RV Shigella RV Shigella RV Shigella Aeromonas (13%) (9%) (3%) (17%) (14%) (69%) (25%) #2 Shigella ETEC ST or E. histolyt V. chol O1 Shigella Aeromon V. chol O1 (13%) LT/ST (5%) (2%) (8%) (11%) (5%) (13%) #3 ETEC ST or NTS Shigella - C. jejuni V. chol O1 C. jejuni LT/ST (8%) (4%) (2%) (10%) (3%) (12%) #4 Noro-GII RV - - V. chol O1 NTS Shigella (8%) (3%) (8%) (2%) (9%) #5 - Crypto - - ETEC ST or - ETEC ST or (3%) LT/ST (7%) LT/ST (5%)“Top 5 - % all cases 38% 22% 7% 24% 44% 77% 51%
  24. 24. Some broad observations • “Top 5” pathogens predominate but differ by age stratum • Specific effective interventions against a small number of pathogens can have a notable impact • New potential priorities identified: – Cryptosporidium – C. jejuni and perhaps Aeromonas in Asia – Adenovirus 40,41? NV GII? • WHO pathogen priority list corroborated – Rotavirus, ETEC, Shigella, V. cholerae O1 • A proportion of diarrhea cases do not have attribution – Other etiologies? Promiscuous antibiotic usage?CVD • All sites & ages, Giardia associated with a significantly lower likelihood of MSD (i.e., appears “protective”)
  25. 25. Probability of MSD case visiting SHC within 7 days of onset (“r”) r is estimated • From pooled HUAS-lite data • Using life table (Kaplan-Meier) analysis, to adjust for HUAS-lite interviews occurring within 7 days of onset of diarrheaCVD
  26. 26. Annual burden (cases & incidence) of adjusted pathogen-attributable MSD, by age, in children age 0-59 mos. in rural Gambia 0-11 m 12-23 m 24-59 m N=5708 N=6230 N=17,139 Total MSD cases 789 1232 513 Adjusted “Top 5” attributable cases 369 561 196 Total MSD rate/100 CYO 13.8 19.8 3.0“Top 5” attributable MSD rate/100 CYO 6.5 9.0 1.1 Rotavirus/100 CYO 3.2 3.4 0.4 Shigella/100 CYO 0.5 2.3 0.4 Cryptosporidium/100 CYO 1.6 1.5 - ETEC LT/ST or ST-only/100 CYO 0.6 1.1 0.3 Norovirus GII/100 CYO 1.0 0.7 0.1 Adenovirus 40,41/100 CYO 0.3 0.5 -
  27. 27. Annual burden of adjusted pathogen-attributable MSD, by age, in children age 0-59 mos. in Pakistan 0-11 m 12-23 m 24-59 m N=4045 N=4653 N=15,827 Total MSD cases 1121 816 452 Adjusted “Top 5” attributable cases 514 381 228 Total MSD rate/100 child years 27.7 17.5 2.9“Top 5” attributable MSD rate/100 CYO 12.7 8.2 1.4 Rotavirus/100 CYO 6.6 1.8 - Aeromonas/100 CYO 2.8 1.9 0.7 Shigella/100 CYO 1.9 2.0 0.2 Vibrio cholerae O1/100 CYO 0.9 1.3 0.4 Cryptosporidium/100 CYO 1.4 1.4 - ETEC LT/ST or ST/100 CYO 2.1 - 0.2 Campylobacter jejuni 1.8 - 0.3 Adenovirus 40/41 0.4 0.6 - Astrovirus 0.8 - -
  28. 28. Annual burden of adjusted pathogen-attributable MSD, by age, in children age 0-59 mos. in Kenya 0-11 m 12-23 m 24-59 m N=3159 N=4746 N=13,698 Total MSD cases 1125 730 690 Adjusted “Top 5” attributable cases 447 251 155 Total MSD rate/100 child years 35.6 15.4 5.0“Top 5” attributable MSD rate/100 CYO 14.2 5.3 1.1 Rotavirus/100 CYO 6.7 2.1 0.2 Cryptosporidium/100 CYO 3.3 1.3 0.1 ETEC LT/ST or ST-only/100 CYO 2.3 1.1 0.2 Shigella/100 CYO 1.5 0.7 0.5 tEPEC/100 CYO 1.7 0.5 - Non-typhoidal Salmonella/100 CYO - 0.6 0.2 Adenovirus 40,41/100 CYO 0.7 - - Entameba histolytica/100 CYO - 0.2 -
  29. 29. Preliminary analysis of mortality data from 24 months of GEMS Pakistani child with severe diarrheal dehydrationCVD
  30. 30. Cases Controls Died Survived CFR Died Survived CFRMozambique 50 630 7.4% 11 1277 0.9%[RR 8.6 (4.5, 16.4)]*Kenya 53 1428 3.6% 11 1877 0.6%[RR 6.1 (3.2, 11.7)]*Gambia 39 991 3.8% 7 1563 0.5%[RR 7.5 (3.8, 18.9)]*Mali 23 2010 1.1% 5 2059 0.2%[RR 4.7 (1.8, 12.3)]*Pakistan 16 1241 1.3% 1 1835 0.1%[RR 23.4 (3.1, 176.0)]*Bangladesh 7 1387 0.5% 1 2464 0.04%[RR 12.4 (1.5, 100.5)] *India 2 1566 0.1% 1 2013 0.1%[RR 2.6 (0.2, 28.3)**Total 190 9253 2.0% 37 13088 0.3%[RR 7.1 (5.0, 10.1)* * p<0.01; **p=0.42
  31. 31. Summary of mortality data • An episode of MSD is associated with a 6- to 7- fold increase in the risk of death within the ensuing ~ 60 days compared to matched controls – Range 2.6-fold in India to 23.4-fold in Pakistan • When deaths occurred: – 35% of deaths occurred within 7 days of enrollment – 65% of deaths occurred > 7 days after enrollment – 33% of deaths occurred > 21 days after enrollment • Where deaths occurred: – 44% of cases died at a medical facility • 26% of cases died during initial SHC encounterCVD – 56% cases died at home or outside a medical facility
  32. 32. Risk factors for fatal diseaseIn a multivariate model, case fatality wasdirectly correlated with:• Younger age• High HIV prevalent sites (Kenya & Mozambique)• Offering less than usual to drink during diarrhea• Low WAZ at enrollment• Isolation of tEPEC, Cryptosporidium
  33. 33. Case fatality by site and age stratum 10 Cases Controls RR 9 0-11m 107 22 5.9 8 12-23m 60 12 6.8 % case fatality 7 6 24-59m 23 3 13.5 5 4 3 2 1 0 Gambia Mali Mozambique Kenya India Bangladesh PakistanCVD
  34. 34. Percent isolation of certain pathogens in fatal and non-fatal MSD cases in infants, by age trimester35 p<0.0001 p=0.0630 Fatal cases25 p=0.06 Survived cases20 p=0.01 p=0.09 p=1.015 p=0.25 p=0.7110 p=0.50 5 0 0-3 mths 4-7 mths 8-11 mths 0-3 mths 4-7 mths 8-11 mths 0-3 mths 4-7 mths 8-11 mths ETEC-ST tEPEC Cryptosporidium
  35. 35. Percent Cryptosporidium isolation in fatal vs 30 non-fatal MSD cases in toddlers 25 25% 20 p=0.0024 Fatal MSD 15 cases 11.4% Survived 10 MSD cases 5 0 12-23 mos
  36. 36. An episode of MSD significantly impacted the linear growth of children • At enrollment, cases were comparable to controls in stature in both continents and all age groups • MSD cases had worse linear growth outcome than controls (comparing anthropometric measurements at enrollment & 60 days) • Africa (-0.11, p = <0.0001)CVD • Asia (-0.07, p=<0.0001)
  37. 37. 0-11 months AFRICA 0-11 months 12-23 months 12-23 months 24-59 months 24-59 months 0 (Cases = closed circles ; Controls=open circles ) (HAZ cases = slope of HAZ change between enrollment and 60-day follow up in cases) -0.2 (HAZ ctrls = slope of HAZ change between enrollment and 60-day follow up in controls) ( slope = difference between mean HAZ cases and HAZ ctrls -0.4 p=NS -0.6  Slope p<0.05 -0.8z score HAZ ctrls P<0.05  Slope <0.05 -1 p=NS  Slope p<0.05 -1.2 HAZ cases p<0.05 p=NS HAZ ctrls p<0.05 HAZ ctrls p<0.05 -1.4 p<0.05 HAZ cases p<0.05 HAZ cases p<0.05 -1.6 -1.8 P=NS p=NS -2 Enrollment Follow-up Enrollment Follow-up Enrollment Follow-up
  38. 38. Serotype Cases % of all case isolates Serotypes of ShigellaS. dysenteriae (any serotype) 55 4.9S. boydii (any serotype) 62 5.5 isolated from 1124S. sonnei 269 23.9 GEMSS. flexneri 1a 3 0.3 cases:S. flexneri 1b 87 7.7 S. dysenteriae – 4.9%S. flexneri 2a 229 20.4S. flexneri 2b 121 10.8 S. boydii – 5.5%S. flexneri 3a 105 9.3 S. sonnei – 23.9%S. flexneri 3b 1 0.1 S. flexneri – 65.7%S. flexneri 4 6 0.5S. flexneri 4a 24 2.1S. flexneri 4b 1 0.1 types 2a + 3a + 6S. flexneri 4c 1 0.1 comprised 457 of 738S. flexneri 5a 0 0.00 S. flexneri strainsS. flexneri 5b 3 0.3S. flexneri 6 123 10.9S. flexneri X 9 0.8 2a+3a+6 + S. sonneiS. flexneri Y 3 0.3 = 65% of all isolates“1c” (S. flexneri 7) 22 2.0
  39. 39. Summary comments Important insights • A small number of pathogens account for ~ one-half of the MSD burden in the first 2 years of life (when mortality risk is highest) • MSD is associated with a 7-fold increase in the risk of death over the ensuing 60 days • Whereas MSD cases & controls are equally stunted upon enrollment, MSD accelerates stunting over the next 60 daysCVD
  40. 40. Proposed actions based on GEMS data • Implement licensed rotavirus vaccines into the EPI of countries in sub-Saharan Africa and South Asia • Implement cholera vaccines in high risk pre-school populations in young children • Given the major role identified for Cryptosporidium as a cause of MSD, invest to develop: – Simple rapid diagnostics – Effective therapyCVD – Vaccines • Implement WASH interventions
  41. 41. ACKNOWLEDGMENTS It takes a global village of investigators, colleagues and wise advisers to complete aCVD study like the GEMS
  42. 42. GEMS Investigators, Mozambique, 2010CVD
  43. 43. International Strategic Advisory Committee (GEMS-ISAC) Co-Chairs: Prof George Griffin, UK; Prof Zulfiqar Bhutta, Pakistan; Prof Fred Binka, Ghana Members: G Armah (Ghana), MK Bhan (India), RE Black (USA), J Breman (USA), WP Chaicumpa (Thailand), T Corrah (Gambia), A Cravioto (Bangladedh), V Curtis (UK), G Dougan (UK), K Earhardt (USA/India), A Grange (Nigeria),G Kang (India), C Lanata (Peru), R Martorell (USA), C Morel (Brazil), C Murray (USA), B Nair (India), MCVD O’Ryan (Chile), P Sansonetti (France), P Smith (UK), M Tanner (Switzerland),
  44. 44. Acknowledgments Many thanks to the superb investigators and staff at each study site, collaborating center, steering committee, and at the CVD coordinating center, to the families who have graciously participated in this study, and to the Bill & Melinda Gates Foundation for financial support.CVD

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