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A Systematic Review and Meta-Analysis of Malaria Test Positivity Outcomes and Programme Interventions in Low Transmission Settings in Southern Africa, 2000–2021

Author

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  • Olukunle O. Oyegoke

    (Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Durban 4000, South Africa)

  • Olusegun P. Akoniyon

    (Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Durban 4000, South Africa)

  • Ropo E. Ogunsakin

    (Biostatistics Unit, Discipline of Public Health Medicine, School of Nursing & Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban 4000, South Africa)

  • Michael O. Ogunlana

    (Department of Physiotherapy, Federal Medical Centre, Abeokuta 110118, Nigeria
    College of Health Sciences, University of KwaZulu-Natal, Durban 4000, South Africa)

  • Matthew A. Adeleke

    (Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Durban 4000, South Africa)

  • Rajendra Maharaj

    (Malaria Research Group, South African Medical Research Council, Durban 4000, South Africa)

  • Moses Okpeku

    (Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Durban 4000, South Africa)

Abstract

Malaria is one of the most significant causes of mortality and morbidity globally, especially in sub-Saharan Africa (SSA) countries. It harmfully disturbs the public’s health and the economic growth of many developing countries. Despite the massive effect of malaria transmission, the overall pooled proportion of malaria positivity rate in Southern Africa is still elusive. Therefore, the objective of this systematic review and meta-analysis is to pool estimates of the incidence of the malaria positivity rate, which is the first of its kind in South African countries. A literature search is performed to identify all published articles reporting the incidence of malaria positivity in Southern Africa. Out of the 3359 articles identified, 17 studies meet the inclusion for systematic review and meta-analysis. In addition, because substantial heterogeneity is expected due to the studies being extracted from the universal population, random-effects meta-analyses are carried out to pool the incidence of the malaria positivity rate from diverse diagnostic methods. The result reveals that between-study variability is high ( τ 2 = 0.003; heterogeneity I 2 = 99.91% with heterogeneity chi-square χ 2 = 18,143.95, degree of freedom = 16 and a p -value < 0.0001) with the overall random pooled incidence of 10% (95%CI: 8–13%, I 2 = 99.91%) in the malaria positivity rate. According to the diagnostic method called pooled incidence estimate, the rapid diagnostic test (RDT) is the leading diagnostic method (17%, 95%CI: 11–24%, I 2 = 99.95%), followed by RDT and qPCR and RDT and loop mediated isothermal amplification (LAMP), respectively, found to be (3%, 95%CI: 2–3%, I 2 = 0%) and (2%, 95%CI: 1–3%, I 2 = 97.94%).Findings of the present study suggest high malaria positive incidence in the region. This implies that malaria control and elimination programmes towards malaria elimination could be negatively impacted and cause delays in actualising malaria elimination set dates. Further studies consisting of larger samples and continuous evaluation of malaria control programmes are recommended.

Suggested Citation

  • Olukunle O. Oyegoke & Olusegun P. Akoniyon & Ropo E. Ogunsakin & Michael O. Ogunlana & Matthew A. Adeleke & Rajendra Maharaj & Moses Okpeku, 2022. "A Systematic Review and Meta-Analysis of Malaria Test Positivity Outcomes and Programme Interventions in Low Transmission Settings in Southern Africa, 2000–2021," IJERPH, MDPI, vol. 19(11), pages 1-17, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:11:p:6776-:d:829824
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    References listed on IDEAS

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    1. Jinkou Zhao & Marcel Lama & Eline Korenromp & Patrick Aylward & Estifanos Shargie & Scott Filler & Ryuichi Komatsu & Rifat Atun, 2012. "Adoption of Rapid Diagnostic Tests for the Diagnosis of Malaria, a Preliminary Analysis of the Global Fund Program Data, 2005 to 2010," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-5, August.
    2. Gillian Stresman & Charlie Whittaker & Hannah C Slater & Teun Bousema & Jackie Cook, 2020. "Quantifying Plasmodium falciparum infections clustering within households to inform household-based intervention strategies for malaria control programs: An observational study and meta-analysis from ," PLOS Medicine, Public Library of Science, vol. 17(10), pages 1-17, October.
    3. Gi-geun Yang & Dohyeong Kim & Anh Pham & Christopher John Paul, 2018. "A Meta-Regression Analysis of the Effectiveness of Mosquito Nets for Malaria Control: The Value of Long-Lasting Insecticide Nets," IJERPH, MDPI, vol. 15(3), pages 1-12, March.
    4. Robert W. Snow & Carlos A. Guerra & Abdisalan M. Noor & Hla Y. Myint & Simon I. Hay, 2005. "The global distribution of clinical episodes of Plasmodium falciparum malaria," Nature, Nature, vol. 434(7030), pages 214-217, March.
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