The effect of COVID-19 on malaria cases in Zambia: a mixed effect multilevel analysis
Open Access
- 22 March 2024
- journal article
- research article
- Published by Springer Nature in Malaria Journal
- Vol. 23 (1) , 1-7
Abstract
Background: The burden of Malaria in Zambia remains a challenge, with the entire population at risk of contracting this infectious disease. Despite concerted efforts by African countries, including Zambia, to implement malaria policies and strategies aimed at reducing case incidence, the region faces significant hurdles, especially with emerging pandemics such as COVID-19. The efforts to control malaria were impacted by the constraints imposed to curb its transmission during the COVID-19 pandemic. The aim of the study was to assess the effect of the COVID-19 pandemic on malaria cases in Zambia and the factors associated by comparing the COVID-19 period and the pre-COVID-19 era. Methods: This was a cross-sectional panel study in which routinely collected programmatic data on malaria was used. The data were extracted from the Health Management Information System (HMIS) for the period January 2018 to January 2022. The period 2018 to 2022 was selected purely due to the availability of data and to avoid the problem of extrapolating too far away from the period of interest of the study. A summary of descriptive statistics was performed in which the number of cases were stratified by province, age group, and malaria cases. The association of these variables with the COVID-19 era was checked using the Wilcoxon rank-sum test and Kruskal‒Wallis test as applicable. In establishing the factors associated with the number of malaria cases, a mixed-effect multilevel model using the Poisson random intercept and random slope of the COVID-19 panel. The model was employed to deal with the possible correlation of the number of cases in the non-COVID-19 panel and the expected correlation of the number of cases in the COVID-19 panel. Results: A total of 18,216 records were extracted from HMIS from January 2018 to January 2022. Stratifying this by the COVID-19 period/era, it was established that 8,852 malaria cases were recorded in the non-COVID-19 period, whereas 9,364 cases were recorded in the COVID-19 era. Most of the people with malaria were above the age of 15 years. Furthermore, the study found a significant increase in the relative incidence of the COVID-19 panel period compared to the non-COVID-19 panel period of 1.32, 95% CI (1.18, 1.48, p < 0.0001). The observed numbers, as well as the incident rate ratio, align with the hypothesis of this study, indicating an elevated incidence rate ratio of malaria during the COVID-19 period. Conclusion: This study found that there was an increase in confirmed malaria cases during the COVID-19 period compared to the non-COVID-19 period. The study also found Age, Province, and COVID-19 period to be significantly associated with malaria cases.Keywords
This publication has 11 references indexed in Scilit:
- Public health-relevant consequences of the COVID-19 pandemic on malaria in sub-Saharan Africa: a scoping reviewMalaria Journal, 2021
- The impact of COVID-19 pandemic on malaria eliminationParasite Epidemiology and Control, 2020
- Managing COVID-19 in Low- and Middle-Income CountriesJAMA, 2020
- The Late Arrival of Coronavirus Disease 2019 (COVID-19) in Africa: Mitigating Pan-continental SpreadClinical Infectious Diseases, 2020
- Malaria: global challenges for malaria eradicationMicrobiology Australia, 2016
- The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015Nature, 2015
- Health Care Systems in Low- and Middle-Income CountriesNew England Journal of Medicine, 2014
- Heterogeneity and cross section dependence in panel data models: theory and applications introductionJournal of Applied Econometrics, 2007
- A conditional analysis for two-treatment multiple-period crossover designs with binomial or poisson outcomes and subjects who drop outStatistics in Medicine, 1993
- Estimation of Dynamic Models with Error ComponentsJournal of the American Statistical Association, 1981