A mathematical model to estimate the incidence of child wasting in Yemen

Author:

Hussein Rana A.,Suprenant Mark P.,Al-Dheeb Najwa,Guerrero Saul,Rogers Eleanor,Shafique Fouzia,Dyson Meredith,Zaman Muhammad H.ORCID

Abstract

Abstract Introduction The ongoing civil war in Yemen has severely restricted imports of food and fuel, disrupted livelihoods and displaced millions, worsening already high pre-war levels of food insecurity. Paired with frequent outbreaks of disease and a collapsed health system, this has brought rates of wasting in children under five to the country’s highest recorded levels, which continue to increase as the crisis worsens and aid becomes increasingly limited. In their planning of services to treat and prevent wasting in children, humanitarian agencies rely on a standard calculation to estimate the expected number of cases for the coming year, where incidence is estimated from prevalence and the average duration of an episode of wasting. The average duration of an episode of moderate and severe wasting is currently estimated at 7.5 months—a globally-used value derived from historical cohort studies. Given that incidence varies considerably by context—where food production and availability, treatment coverage and disease rates all vary—a single estimate cannot be applied to all contexts, and especially not a highly unstable crisis setting such as Yemen. While recent studies have aimed to derive context-specific incidence estimates in several countries, little has been done to estimate the incidence of both moderate and severe wasting in Yemen. Methods In order to provide context-specific estimates of the average duration of an episode, and resultingly, incidence correction factors for moderate and severe wasting, we have developed a Markov model. Model inputs were estimated using a combination of treatment admission and outcome records compiled by the Yemen Nutrition Cluster, 2018 and 2019 SMART surveys, and other estimates from the literature. The model derived estimates for the governorate of Lahj, Yemen; it was initialized using August 2018 SMART survey prevalence data and run until October 2019—the date of the subsequent SMART survey. Using a process of repeated model calibration, the incidence correction factors for severe wasting and moderate wasting were found, validating the resulting prevalence against the recorded value from the 2019 SMART survey. Results The average durations of an episode of moderate and severe wasting were estimated at 4.86 months, for an incidence correction factor k of 2.59, and 3.86 months, for an incidence correction factor k of 3.11, respectively. It was found that the annual caseload of moderate wasting was 36% higher and the annual caseload of severe wasting 58% higher than the originally-assumed values, estimated with k = 1.6. Conclusion The model-derived incidence rates, consistent with findings from other contexts that a global incidence correction factor cannot be sufficient, allow for improved, context-specific estimates of the burden of wasting in Yemen. In crisis settings such as Yemen where funding and resources are extremely limited, the model’s outputs holistically capture the burden of wasting in a way that may guide effective decision-making and may help ensure that limited resources are allocated most effectively.

Funder

UNICEF

Undergraduate Opportunities Program (UROP), Boston University

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health,Health(social science)

Reference24 articles.

1. Brück T, D’errico, M. . Food security and violent conflict: introduction to the special issue. World Dev. 2019;117:167–71. https://doi.org/10.1016/j.worlddev.2019.01.007.

2. Martins VJ, Toledo Florêncio TM, Grillo LP, do Carmo PFM, Martins PA, Clemente AP, Santos CD, de Fatima AVM, Sawaya AL. Long-lasting effects of undernutrition. Int J Environ Res Publ Health. 2011;8(6):1817–1846.https://doi.org/10.3390/ijerph8061817

3. “Yemen: Acute Food Insecurity Situation October - December 2020 and Projection for January - June 2021 : IPC Global Platform.” IPC Portal, www.ipcinfo.org/ipc-country-analysis/details-map/en/c/1152947/.

4. Yemeni children suffer record rates of acute malnutrition, putting 'entire generation' at risk | | UN News. (n.d.). Retrieved November 09, 2020, from https://news.un.org/en/story/2020/10/1076272

5. Overview on Acute Malnutrition and Food Insecurity among Children during the Conflict in Yemen. Children (Basel, Switzerland). 6(6):77. https://doi.org/10.3390/children6060077

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