Comparative analyses revealed reduced spread of COVID-19 in malaria endemic countries

  1. Azhar Muneer
  2. Kiran Kumari
  3. Manish Tripathi
  4. Rupesh Srivastava
  5. Asif Mohmmed
  6. Sumit Rathore

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Abstract

In late 2019, SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) infection started in Hubei province of China and now it has spread like a wildfire in almost all parts of the world except some. WHO named the disease caused by SARS-CoV-2 as COVID-19 (CoronaVirus Disease-2019). It is very intriguing to see a mild trend of infection in some countries which could be attributed to mitigation efforts, lockdown strategies, health infrastructure, demographics and cultural habits. However, the lower rate of infection and death rates in mostly developing countries, which are not placed at higher levels in terms of healthcare facilities, is a very surprising observation. To address this issue, we hypothesize that this lower rate of infection is majorly been observed in countries which have a higher transmission/prevalence of protozoan parasite borne disease, malaria. We compared the COVID-19 spread and malaria endemicity of 108 countries which have shown at least 200 cases of COVID-19 till 18th April 2020. We found that the number of COVID-19 cases per million population correlates negatively with the malaria endemicity of respective countries. The malaria free countries not only have higher density of COVID-19 infections but also the higher case fatality rates as compared to highly malaria endemic countries. We also postulate that this phenomenon is due to natural immune response against malaria infection, which is providing a heterologous protection against the virus. Unfortunately, there is no licensed vaccine against SARS-CoV-2 yet, but this information will be helpful in design of future strategies against fast spreading COVID-19 disease.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.11.20097923: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data was plotted and analyzed using Graphpad prism and R package based statistical analyses.
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.05.11.20097923v1 on medRxiv