Socioeconomic, demographic and environmental factors inform malaria intervention prioritization in urban Nigeria

Author:

Chiziba Chilochibi1,Diallo Ousmane1,Bertozzi-Villa Amelia2,Weiss Dan3,Mercer Laina4,Gerardin Jaline1,Ozodiegwu Ifeoma D.1

Affiliation:

1. Northwestern University

2. Institute for Disease Modeling

3. Telethon Kids Institute, Perth Children’s Hospital

4. PATH

Abstract

Abstract Background Nigeria is one of three countries projected to have the largest absolute increase in the size of its urban population and this could intensify malaria transmission in cities. Accelerated urban population growth is outpacing the availability of affordable housing and basic services and resulting in living conditions that foster vector breeding and heterogeneous malaria transmission. Understanding community determinants of malaria transmission in urban areas informs the targeting of interventions to populations at greatest risk. Methods In this study, we analyzed cluster-level data from the Demographic and Health Surveys (DHS) and the Malaria Indicator Survey (MIS) as well as geospatial covariates to describe malaria burden and its determinants in areas administratively defined as urban in Nigeria. Univariate and multivariable models were respectively used to identify potential intervention prioritization thresholds and likely casual impact of individual variables. Results Overall, we found low malaria test positivity across urban areas. We observed declines in test positivity rate over time and identified the percentage of individuals with post-primary education, the percentage of individuals in the rich wealth quintiles, the percentage of individuals living in improved housing in 2015, all age population density, median age, the percentage of children under the age of five that sought medical treatment for fever, total precipitation, and enhanced vegetation index as key community predictors of malaria transmission intensity. Conclusions The unrepresentativeness of the DHS and MIS in urban settings at the state and geopolitical zonal level, regional differences in malaria seasonality across Nigeria, and information detection bias were among likely factors that limited our ability to compare malaria burden across geographic space and ultimately drove model uncertainty. Nevertheless, study findings provide a starting point for informing decisions on intervention prioritization within urban spaces and underscore the need for improved regionally focused surveillance systems in Nigeria.

Publisher

Research Square Platform LLC

Reference51 articles.

1. World Health Organization. World Malaria Report 2021. Geneva. ; 2021. Available: https://www.who.int/publications/i/item/9789240040496

2. Spatio-temporal analysis of association between incidence of malaria and environmental predictors of malaria transmission in Nigeria;Okunlola OA;Sci Rep,2019

3. National Malaria Control Programme, Organization suMAPWHealth. INFORM project. A description of the epidemiology of malaria to guide the planning of control in Nigeria. A report prepared for the Federal Ministry of Health, Nigeria, the Roll Back Malaria Partnership and the Department for International Development, UK. 2013. Available: https://web-archive.lshtm.ac.uk/www.linkmalaria.org/sites/link/files/content/attachments/2018-07-27/Nigeria profile 2013.pdf

4. Evaluating the effects of climate and environmental factors on under-5 children malaria spatial distribution using generalized additive models (GAMs);Jane Ugwu CL;J Epidemiol Glob Health,2020

5. United Nations Department of Economic and Social Affairs. World Urbanization Prospects: The 2018 Revision. World Urbanization Prospects: The 2018 Revision. 2019. doi:10.18356/b9e995fe-en

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