Estimating the burden of wasting during COVID-19 based on empirical experiences in the Sahel
By Saidou Magagi, Sumra Kureishy, Jessica Bourdaire and Katrien Ghoos
Saidou Magagi is a monitoring, evaluation and knowledge management officer for nutrition at the World Food Programme’s regional office for West and Central Africa.
Sumra Kureishy is a nutrition officer at the World Food Programme’s regional office for West and Central Africa.
Jessica Bourdaire is a Nutrition Research Officer at the Nutrition Division of the World Food Programme’s Headquarters.
Katrien Ghoos is a senior regional nutrition adviser at the World Food Programme’s regional office for West and Central Africa.
World Food Programme RBD would like to acknowledge the collaborating partners of the model presented in this article, including UNICEF and European Civil Protection and Humanitarian Aid Operations (ECHO), as well as the donors, the governments and the food security and nutrition working groups/clusters.
Location: Burkina Faso, Mali, Mauritania, Niger, Chad and Senegal.
What we know: An incidence correction factor (K) of 1.6 is generally used to estimate the burden of wasting; some countries report that this leads to underestimates.
What this article adds: A revised mathematical model was developed to address a perceived risk of underestimation of the burden of wasting in the six Sahelian countries. Drawing on previous work, a mathematical model was devised to improve estimates and account for food insecurity, seasonal variation and the impact of COVID-19. It drew upon existing national and regional admissions data from community-based management of acute malnutrition programmes (2014-2019), prevalence data from nutrition surveys, population data from national censuses and food and nutrition insecurity data from the Cadre Harmonisé. Programme coverage was assumed to be 100% to estimate the total burden for the period covering April to December 2020. Estimations for 2020 found a burden of 5.35 million wasted children, higher than the 4.54 million originally projected. The mathematical model allowed for the estimation of region-specific incidence correction factors per quarter accounting for food insecurity, seasonal variations and COVID-19.
Wasting is a global public health problem that results in increased child morbidity and mortality. It was estimated in 2019 that the global prevalence of wasting in children under five years of age was 47 million, with a prevalence of 7.9 million wasted children in West and Central Africa (UNICEF, WHO & World Bank, 2020). Prevalence is estimated through cross-sectional surveys. However, as prevalence data is based on a snapshot in time, some cases will be missed and the number of children affected by wasting underestimated. Incidence estimates, captured through longitudinal cohort studies, capture new cases over time and are therefore a more accurate estimate of the burden (Insanaka et al, 2016). When longitudinal studies are unavailable, burden can be estimated using the context-specific relationship between prevalence and incidence (Bulti et al, 2017). The average duration of disease reflects when a prevalent case has recovered or dies or has moved out of the population of interest. When the incidence is stable for the duration of the disease, prevalence is estimated as a product of incidence and the average duration of disease. Hence, through simple substitutions, the burden simplifies to the population size, prevalence and incidence correction factor (K). Box 1 provides details on the current formula used to estimate the burden of wasting in this way (Bulti et al, 2017).
Box 1: Current formula used to estimate burden of wasting
Research shows that governments, United Nations (UN) agencies and community-based management of acute malnutrition (CMAM) implementing partners around the world use 7.5 months as the average duration of an untreated severe acute malnutrition episode for a one-year planning period which provides an incidence correction factor (K) of 1.6 (Garenne et al, 2009). However, some countries have recently reported that the use of this single K has led to burden underestimation (Bulti et al, 2017).
An urgent request was made to the World Food Programme (WFP) regional office for West and Central Africa by the regional (West Africa) Food Security and Nutrition Working Group (FSNWG)1 in 2020 to address any risk of underestimating the burden of wasting for the G5+1 Sahel countries (Burkina Faso, Mali, Mauritania, Niger, Chad and Senegal) as a result of the COVID-19 pandemic and accounting for food insecurity and seasonal variation. In response, we developed a mathematical model, based on the burden model developed by Mark Myatt (Myatt, 2012) and regional experiences. This article outlines the steps taken and the equations used to obtain this revised model for burden estimation.
Sources of data and assumptions
The model was generated based on the experiences and lessons learned from previous burden analyses carried out and existing national and regional CMAM admissions data from the previous five years (2014-2019), prevalence data from nutrition surveys in the G5+1 countries, population data from national censuses and food and nutrition insecurity data from the Cadre Harmonisé.2 Programme coverage was assumed to be 100% as the model aimed to estimate the total burden for the period covering April to December 2020. The model was reviewed for technical validity and endorsed by the regional FSNWG.
With the rise in the number of wasted children aged 6 to 59 months during the lean season (April-September) and regional experiences dictating a wide variation in the average duration of an episode of wasting, the regional FSNWG, along with national nutrition and food security clusters, agreed that the proposed pattern of wasting and the average duration of an episode should be based on standard calendar quarters.3 Moreover, since the pandemic was only declared after March 2020, the incidence correction factor of K=1.6 was used to estimate the burden of wasting in quarter one.
Steps to adjust for food insecurity, seasonal variation and COVID-19
The average duration of a wasting episode was estimated as the product of the planning period per quarter (Qn) and the quotient of the global average duration of an untreated episode (7.5 months) for a one-year planning period (Box 2, equation 1). Mean smoothing of the three months of each quarter was applied to the average duration of an untreated episode to reduce and control for random variation (STE) (Box 2, equation 2). The incidence correction factor per quarter adjusted for food insecurity was calculated as the quotient of the planning period per quarter (Qn) and the smoothed average duration of an untreated episode (STE) (Box 2, equation 3). The burden of wasting was then adjusted based on the incidence correction factor for food insecurity per quarter (FSQn), as detailed in Box 2 (equation 4). To adjust for seasonal variation, admissions data from the previous five years was analysed and the mean was smoothed to determine the burden averaged across the previously mentioned quarters (Qn) (Box 2, equation 5).
To determine the impact of the COVID-19 pandemic on the burden of wasting, experiences and CMAM, admissions data from the Ebola crisis (2014-2016) and World Health Organization data (WHO, 2016) were used to forecast an increase in the expected number of new cases for each quarter (Box 2, equation 6). The approach was then used to estimate the burden of wasting adjusted for food insecurity, seasonal variation and COVID-19 for the period of April to December 2020 (Box 2, equation 7).
In the first step, estimating the smoothed duration of an episode for food insecurity per quarter, the incidence correction factors were found to be 1.6, 1.85, 2.06 and 2.18, respectively. Table 1 shows the resulting adjusted incidence correction factors for food insecurity per quarter. These correction factors were found to increase substantially per quarter; the correction factor K increased more than 30% by the fourth quarter. The second estimation step found an attribution of 20-25% from seasonal variation on the burden of wasting.
Table 1: Estimates of the adjusted incidence correction factor for food insecurity per quarter
For the impact of COVID-19 on wasting, the third estimation step found an increase in the initial expected number of new cases by 0% in Quarter 1, 10% in Quarter 2, 15% in Quarter 3 and 20% in Quarter 4. This step accounts for the negative impact of the restrictive measures on access to healthcare, delays in the diagnosis and treatment of wasting, access to food supplies and other socio-economic aspects (WFP, 2020).
Table 2 shows the initial burden of wasting, calculated using an incidence correction factor of 1.6 and the revised burden adjusted for food insecurity, seasonal variation and COVID-19 for 2020. The burden of wasting calculated with a K=1.6 was found to have vastly underestimated the annual burden of wasting by about 0.8 million children. This corresponds to an underestimation of 18% of the burden initially forecasted for April to December 2020.
Table 2: Wasting burden estimates for 2020 adjusted for food insecurity, seasonal variation and the impact of COVID-19 in G5+1 Sahel countriesa
The improved burden estimates were used to identify priority geographical areas in need of urgent assistance. Overall, the revised burden estimates enabled the region to adjust and orient planned activities and resources to address wasting in the hardest hit areas.
Similarly, the G5+1 countries were able to use the revised burden estimates to inform national hotspot analyses which led to the early identification of priority areas and to the adaptation of the WFP's wasting prevention and treatment response. These adaptations led WFP to increase its reach to beneficiaries by an additional 15 to 30% across the six countries. Moreover, the revised burden estimates have been used to guide regional research, such as the ongoing Fill the Nutrient Gap analysis which identifies and models multi-sector approaches to prevent malnutrition in the Sahel.
Through clear and organised consultations and consensus building with countries (governments, non-governmental organisations and UN agencies), the revised model was able to generate estimates in a coordinated manner and ensure buy-in, a key lesson learned during this experience.
Evidence-based decision-making is essential to creating sustainable change and, given the COVID-19 pandemic, the model enabled the region to produce adequate burden estimates. By applying standard calendar quarters, the model was able to account for the seasonal variation observed in the burden of wasting across the Sahel region.
The revised mathematical model presented in this article allowed for the estimation of region-specific incidence correction factors per quarter accounting for food insecurity, seasonal variations and COVID-19. The quarterly values of correction factors estimated for 2020 based on population, prevalence and coverage data from 2014 to 2019 found a burden of 5.35 million wasted children which appears to be a more accurate estimate of the burden than the 4.54 million originally estimated. In the absence of up to date health and nutrition data during COVID-19, this approach using incidence correction factors adjusted for food insecurity, seasonal variation and COVID-19 may be considered for improving burden estimates of wasting in G5+1 Sahel countries.
For more information, please contact Katrien Ghoos at email@example.com.
1 The regional Food Security and Nutrition Working Group (FSNWG) is based in Dakar, Senegal. Under the coordination of the Office for the Coordination of Humanitarian Affairs, it consists of the regional representation of UN agencies, donors, and international non-government organisations who have interventions in West and Central Africa.
2 The Cadre Harmonisé is West Africa’s equivalent to the Integrated Phase Classification (IPC) which provides a meta-analysis of data from existing information systems on agriculture, household economy, food consumption patterns, health and nutrition to classify the severity of acute food and nutrition insecurity.
3 The standard calendar quarters were defined as January – March (quarter 1), April – June (quarter 2), July – September (quarter 3) and October – December (quarter 4); the planning periods per quarter were defined as 3 months for quarter 1, 6 months for quarter 2, 9 months for quarter 3 and 12 months for the last quarter.
Bulti, A, Briend, A, Dale, N M, De Wagt, A, Chiwile, F, Chitekwe, S, Isokpunwu, C, Myatt, M (2017) Improving estimates of the burden of severe acute malnutrition and predictions of caseload for programs treating severe acute malnutrition: experiences from Nigeria. Archives of Public Health 75:66
Garenne, M, Willie, D, Maire, B, Fontaine, O, Eeckels, R, Briend, A, Van den Broeck, J (2009) Incidence and duration of severe wasting in two African populations. Public Health Nutr. 2009;12(11):1974–82.
Isanaka, S, Boundy, E, Grais, R F, Myatt, M and Briend, A (2016) Improving Estimates of Numbers of Children With Severe Acute Malnutrition Using Cohort and Survey Data. Am J Epidemiol. 2016;184(12):861–869
Myatt, M (2012) How do we estimate caseload for SAM and / or MAM in children 6 – 59 months in a given time period? Retrieved from: https://www.humanitarianresponse.info/sites/www.humanitarianresponse.info/files/documents/files-/caseload_cmam-june-2012.pdf
UNICEF, World Health Organization and the World Bank (2020) UNICEF-WHO-World Bank Joint Child Malnutrition Estimates. UNICEF, New York; WHO, Geneva; The World Bank, Washington, DC.
World Food Programme (2020) Update on the impact of Covid-19 on food and nutrition security in West and Central Africa. World Food Programme. Retrieved from: http://www.food-security.net/en/document/update-on-the-impact-of-covid-19-on-food-and-nutrition-security-in-west-and-central-africa/
World Health Organization (2016) Ebola data and statistics - situation summary. World Health Organization. Retrieved from: https://apps.who.int/gho/data/view.ebola-sitrep.ebola-summary-latest.%20Accessed%20on%20December%2030
Box 2: Revised formula for the calculation of the burden of wasting based on the adjusted incidence correction factor for food insecurity, seasonal variation and COVID-19 per quarter
More like this
View this article as a pdf Dear readers, A warm welcome to the 65th edition of Field Exchange. This edition features a range of programming issues that unfortunately reflect...
FEX: Improving estimates of numbers of children with severe acute malnutrition using cohort and survey data
Summary of Research Isanaka S, Boundy EO, Graise RF, Myatt M and Briend A. (2016). Improving Estimates of Numbers of Children With Severe Acute Malnutrition Using Cohort and...
I'm currently training some folks on how to calculate expected CMAM caseload using the (prevalence + incidence) * coverage equation. I'm having difficulty explaining to my team...
FEX: Calculating wasting caseloads and geographic prioritisation of nutrition services in the context of limited data in Afghanistan
View this article as a pdf By Beka Teshome Bongassie, Said M Yaqoob Azimi and Maureen L. Gallagher Beka Teshome is Nutrition Cluster co-lead for Afghanistan with Action...
From a document found in CMAM Forum on how to calaculate the SAM/ or MAM, The formula is: Case load = N × P × K × C N= total population of the under-fives in the catchment...
Summary of commentary1 Authors of an invited commentary on a recent paper by Isanaka et al (2016), that described development of an updated incidence-correction factor for...
We are currently calculating people in need (PiN) as per the humanitarian needs overview (HNO). The two most recent large scale national nutrition surveys indicated GAM rates...
View this article as a pdf Lisez cet article en français ici By Harriet Torlesse and Minh Tram Le Background Each annual release of the Joint Malnutrition Estimates...
View this article as a pdf Lisez cet article en français ici By Harriet Torlesse, Roland Kupka, Warren T K Lee, Britta Schumacher and Angela de Silva Harriet Torlesse...
Summary of report1 Thanks to Saul Guerrero, ACF-UK, for preparing this summary. Location: Global What we know: Mapping of global SAM management requires baseline and...
FEX: COVID-19 pandemic and mitigation strategies: implications for maternal and child health and nutrition
View this article as a pdf Research Snapshot1 The adverse global impact of COVID-19 on poverty, the coverage of essential support services and access to nutritious foods is...
View this article as a pdf Research snapshot1 The COVID-19 pandemic will likely increase the risk of all forms of malnutrition as a result of rapid changes to the...
FEX: Incidence correction factors for moderate and severe acute child malnutrition from two longitudinal cohorts in Mali and Burkina Faso
View this article as a pdf Research snapshot1 Accurate estimates of the burden of acute malnutrition (AM) are essential to support policy makers and nutrition programmers in...
View this article as a pdf Click here to listen to an interview with one of the authors on the ENN podcast channel Summary of research1 What we know: Cross-sectional,...
By Safari Balegamire (VALID International), Katja Siling (World Food Programme), Jose Luis Alvarez Moran (Coverage Monitoring Network), Ernest Guevarra (VALID International),...
View this article as a pdf Lisez cet article en français ici A warm welcome to our 63rd edition of Field Exchange, focused on child wasting in South Asia. The idea for...
FEX: Effect of adding RUSF to ageneral food distribution on child nutritional status and morbidity: a cluster randomised controlled trial
Summary of research1 Child during appetite test at a health facility offering treatment in Monrovia, Liberia The authors of a recent study hypothesized that including a daily...
UNICEF has issued a request to organisations to share data to inform an analysis of the incidence of severe acute malnutrition (SAM) at country level. This analysis aims to...
FEX: Remote Integrated Phase Classification during the COVID-19 pandemic: experiences from Madagascar
View this article as a pdf By Smaila Gnegne, Moussa Moctar, Andrianianja Raonivelo, Desire Rwodzi, Mara Nyawo and Douglas Jayakasekaran Smaila Gnegne is a health statistician...
The Global Technical Assistance Mechanism for Nutrition (GTAM) is a common global mechanism endorsed by over 40 Global Nutrition Cluster (GNC) partners that aims to improve the...
Reference this page
Saidou Magagi, Sumra Kureishy, Jessica Bourdaire and Katrien Ghoos (). Estimating the burden of wasting during COVID-19 based on empirical experiences in the Sahel. Field Exchange 65, May 2021. p89. www.ennonline.net/fex/65/burdenofwastingcovid19sahel