This document analyzes community vulnerability to COVID-19 in Malawi using spatial data. It finds the Southern Region and several districts within have the highest overall vulnerability due to factors like high stunting rates, low food expenditures, and poor access to healthcare. Urban areas like cities face high vulnerability from population density. Food price changes in 2020 decreased demand for key micronutrients in both rural and urban households, with a larger impact on rural areas, potentially exacerbating existing micronutrient deficiencies. The analysis identifies priority areas for crisis prevention and mitigation based on chronic vulnerability.

1. Assessing Community Vulnerability
to COVID-19 in Malawi: A Spatial
Outlook
Dr. John Ulimwengu, Africawide ReSAKSS Coordinator
With analysis by Dr. Greenwell Matchaya, Sibusiso Nhlengethwa, Léa Magne Domgho
April 28, 2021

2. Outline
I. Community vulnerability analysis
• Introduction
• Methodology
• Findings
• Conclusion
• Implications
II. Effects of Covid-19 on micronutrient demand

3. I. Community vulnerability analysis
Introduction (1)
• The impacts of crises are especially severe in areas where chronic
vulnerability is high.
• Understanding patterns of vulnerability is thus of major importance
to guide strategies to prepare for and respond to crises.
• Our goal is to identify areas which, if affected by Covid, would have
the least capacity to absorb shocks and would face the most serious
consequences.
3

4. Introduction (2)
• This study focuses on differentiated spatial vulnerability in Malawi
using an overlay of indicators:
• Susceptibility to the spread of the disease: Population density; disease burden
• Inability to care for infected people: Health infrastructure
• Existing food and nutrition insecurity: Child undernutrition, food consumption
• Due to limited resources, the most vulnerable communities should be
prioritized in crisis prevention and mitigation efforts.

5. Methodology (1)
• The study used 3 Administrative Regions of
the country and all the 28 Districts therein
(2019)
I. Northern
II. Central
III. Southern
• The 28 districts are:
• Northern Region: Chitipa, Karonga, Likoma, Mzimba,
Nkhata & BayRumphi
• Central Region: Dedza, Dowa, Kasungu, Lilongwe,
Mchinji, Nkhotakota, Ntcheu, Ntchisi & Salima
• Southern Region: Balaka, Blantyre, Chikwawa,
Chiradzulu, Machinga, Mangochi, Mulanje, Mwanza,
Neno, Nsanje, Phalombe, Thyolo & Zomba

6. Methodology (2)
Various data sources were considered:
Variable Description DATA SOURCE
hfa2 Height-for-age (Prevalence of stunting)
Demographic and Health Survey
(DHS) 2017
Wfa2 Weight-for-age (Prevalence of Underweight) (DHS) 2017
Wfh2 Wight-for-height (Prevalence of wasting) (DHS) 2017
diab Prevalence of diabetes (DHS) 2017
bloodp Prevalence of high blood pressure (DHS) 2017
Assis_pp
Proportion of females (15-49) getting assistance from doctor,
nurse/midwife, (DHS) 2017
medhelp_disthf
Proportion of females (15-49) for whom distance to health facility
is a big problem (DHS) 2017
pcfood Food expenditure per capita Malawi Housing Census (2018)
density_pop_sup Density of inhabited areas (estimated through remote sensing) Malawi Housing Census (2018)

7. Findings (1): Country vulnerability index
• The composite vulnerability index
suggests that chronic vulnerability is
highest in the Southern Region and
lowest in the Northern Region.

8. Findings (2): Stunting
• The prevalence of stunting is highest in 9
districts (Dedza, Neno, Mchinji, Zomba
Rural, Ntcheu, Mangochi, Mzimba,
Lilongwe Rural and Ntchisi).
• 6 districts (Likoma, Blantyre City, Karonga,
Zomba City, Lilongwe City, and Mzuzu City)
have lower proportions of stunting and are
hence considered much less vulnerable

9. Findings (3): Food consumption per capita
• 8 districts (Mulanje, Machinga, Thyolo,
Nsanje, Chikwawa, Chradzulu, Chitipa,
and Phalombe) spend the least on
food and are considered much more
vulnerable.
• These are mostly Southern region
districts.

10. Findings (4): Access to health services
• Nsanje, Mangochi, Salima, Nkhotakota, Ntcheu, Mzimba,
and Lilongwe Rural districts have very low proportions of
women receiving assistance from a medical professional
during birth.
• Lilongwe Rural, Phalombe, Machinga, Balaka, Mchinji Dowa,
and Neno have the highest proportions of women who stated
that distance was a challenge in accessing healthcare.

11. Findings (5): Disease Burden
• Mzuzu City, Lilongwe City, Balaka, Dowa, Neon,
Thyolo, Nkhatabay and Likoma have higher
proportions of people with blood pressure
problems.
• Mzuzu City, Mchinji, Zomba City, Nkhotakota,
Dedza, Blantyre Rural, Blantyre City, Lilongwe City
and Chikwawa have the highest proportions of
people with diabetes.

12. Findings (6): Population density
• All the cities (Blantyre City, Lilongwe City,
Mzuzu City, and Zomba City) have very
high population densities, thus making
them much more vulnerable to COVID-19
impacts.

13. II. Effects of Covid-19 on micronutrient demand
• Covid-19-related price changes affect nutrition through
their impacts on demand for key micronutrients.
• We estimate micronutrient price elasticities and apply
them to actual 2020 price changes to predict impacts on
micronutrient demand.

14. Price changes in April-November 2020
• Prices of several staple foods
stayed constant or fell
slightly in April-Nov 2020
• Maize prices increased in
urban and rural areas
• This increase followed a
sharp decline in maize prices
in March -10
0
10
20
30
40
50
60
Beans Groundnuts
(shells)
Maize Rice
Malawi food price changes, April-November
2020 (percent)
Urban Rural

15. Existing micronutrient deficiencies
• Households consume close to
the recommended level of
protein, calcium, and iron.
• Consumption of calories and
other key nutrients is
inadequate, especially for
Vitamins B12 and A.
• Deficiencies are more severe in
rural areas.
Note: AME = Adult Male Equivalent

16. Price elasticities of calories and micronutrients
-0,80
-0,60
-0,40
-0,20
0,00
0,20
Calories Protein Calcium Iron Zinc Folate Vitamin B12 Vitamin A
Rural
Cereals & Products Roots, Tubers, and Plantains Nuts and Pulses Vegetables
Meat, Fish & products Fruits Milk and Products Cooked Foods from Vendors
Sugar & sweet Oils and Fats Beverages Spices & Miscellaneous
-0,80
-0,60
-0,40
-0,20
0,00
0,20
0,40
Calories Protein Calcium Iron Zinc Folate Vitamin B12 Vitamin A
Urban
Cereals & Products Roots, Tubers, and Plantains Nuts and Pulses Vegetables
Meat, Fish & products Fruits Milk and Products Cooked Foods from Vendors
Sugar & sweet Oils and Fats Beverages Spices & Miscellaneous
• In most cases, demand
for nutrients falls when
food prices rise
• Demand for calories,
protein and zinc is most
sensitive to changes in
cereals prices
• Demand for calcium,
iron, and vitamin B12 is
especially sensitive to
changes in meat and
fish prices
• Demand for Vitamin A
is sensitive to changes
in vegetable prices

17. Impact of 2020 food price changes on nutrient demand
• Price changes in April-November 2020 are expected to decrease households’
demand for key micronutrients, especially calories, protein, zinc and folate.
• Decreases in demand are larger for rural than for urban households.

18. Key Messages
• The impacts of crises are especially severe in areas where chronic
vulnerability is high.
• Understanding patterns of vulnerability is thus of major importance
to guide strategies to prepare for and respond to crises.
• Our goal is to identify areas which, if affected by Covid, would have
the least capacity to absorb shocks and would face the most serious
consequences.
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19. Key Messages (continued)
• We construct an indicator to measure the level of vulnerability to
serious food security consequences of Covid-19.
• Three components: Susceptibility to the spread of the disease,
inability to care for infected people, and existing food and
nutrition insecurity.
• We identify areas of particular concern where governments should
focus crisis monitoring and mitigation efforts.
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20. Key Messages (continued)
• Changes in price during 2020 modestly affected consumption of key
micronutrients, including calories, protein, zinc and folate.
• Even small changes could exacerbate existing micronutrient
deficiencies.
• Effects were larger in rural areas, which also suffer from greater
existing micronutrient deficiencies.
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21. THANK YOU
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