Tuberculosis Prevalence Correlation to COVID-19 Mortality in Malaria Free Countries

Background: Both malaria and latent tuberculosis ( LTB) are possible factors related to decreased COVID-19 mortality. The malaria endemicity variable is a possible confounder when conducting a study on the correlation of LTB prevalence to COVID-19 mortality. Studies regarding LTB prevalence" according to different studies" did not adjust malaria endemicity as a possible confounder. Many malaria-endemic countries are high TB prevalent. Malaria-free countries could be: high, moderate, or low in TB prevalence. The main aim of this study is to look for the influence of TB prevalence on COVID-19 mortality. TB prevalence reflects LTB prevalence in the absence of malaria endemicity as a possible confounding factor in TB studies. Material and methods: The total chosen countries were 69 non-malaria endemic countries. Countries were classified according to TB prevalence groups into low, moderate, and high prevalent groups. Covid-19 deaths/Million(M) inhabitants were taken as reported on September 2, 2020. "Kendall's-τ Correlation Coefficient", "Kruskal-Wallis test, and Mann-Whitney test were used in statistical analyses.Results: We found inverse relationships between TB prevalence and COVID-19 deaths/ (M) inhabitants and a highly positive significant correlation coefficient was reported (0.008) in Kendall's-τ correlation coefficient test. Kruskal-Wallis test showed a significant relationship within studied groups. Furthermore, the low TB prevalent group had significant reverse associations with both high and moderate TB prevalent groups in the Mann-Whitney test.Conclusion: In the absence of possible malaria confounding, TB prevalence in malaria-free countries is inversely related to COVID-19 mortality in a highly significant association.

Predictive markers of transmission in areas with different malaria endemicity in north-eastern Tanzania based on seroprevalence of antibodies against Plasmodium falciparum

Objective A community-based cross-sectional study was done to assess Plasmodium falciparum exposure in areas with different malaria endemicity in north-eastern Tanzania using serological markers; PfAMA-1 and PfMSP-119. Results Bondo had a higher seroprevalence 36.6% (188) for PfAMA-1 as compared to Hai 13.8% (33), χ2 = 34.66, p < 0.01. Likewise, Bondo had a higher seroprevalence 201(36.6%) for PfMSP-1 as compared to Hai 41 (17.2%), χ2 = 29.62, p < 0.01. Anti-PfAMA-1 titters were higher in malaria positive individuals (n = 47) than in malaria negative individuals (n = 741) (p = 0.07). Anti-PfMSP-1 antibody concentrations were significantly higher in malaria-positive individuals (n = 47) than in malaria-negative individuals (n = 741) (p = 0.003). Antibody response against PfAMA-1 was significantly different between the three age groups; < 5 years, 5 to 15 years and > 15 years in both sites of Bondo and Hai. Likewise, antibody response against PfMSP-119 was significantly different between the three age groups in the two sites (p < 0.001). We also found significant differences in the anti-PfAMA-1and anti-PfMSP-119 antibody concentrations among the three age groups in the two sites (p = 0.004 and 0.005) respectively. Immunological indicators of P. falciparum exposure have proven to be useful in explaining long-term changes in the transmission dynamics, especially in low transmission settings.

Predictive markers of transmission in areas with different malaria endemicity in north-eastern Tanzania based on seroprevalence of antibodies against Plasmodium falciparum

Objective The objective of this study was to assess Plasmodium falciparum exposure in areas with different malaria endemicity in north-eastern Tanzania using serological markers; PfAMA-1 and PfMSP-119.Results Bondo had a higher seroprevalence 36.6% (188) for PfAMA-1 as compared to Hai 13.8% (33), χ2=34.66, p<0.01. Likewise, Bondo had a higher seroprevalence 201(36.6%) for PfMSP-1 as compared to Hai 41 (17.2%), χ2 =29.62, p<0.01. Anti-PfAMA-1 titters were higher in malaria positive individuals (n = 47) than in malaria negative individuals (n = 741) (p = 0.07). Anti-PfMSP-1 antibody concentrations were significantly higher in malaria-positive individuals (n = 47) than in malaria-negative individuals (n = 741) (p = 0.003).Antibody response against PfAMA-1 was significantly different between the three age groups; <5 years, 5 to 15 years and >15 years in both sites of Bondo and Hai. Likewise, antibody response against PfMSP-119 was significantly different between the three-age groups in the two sites. (p<0.001). We also found significant differences in the anti-PfAMA-1and anti-PfMSP-119 antibody concentrations among the three age groups in the two sites (p=0.004 and 0.005) respectively. Immunological indicators of Plasmodium falciparum exposure have proven to be useful in explaining long-term changes in the transmission dynamics especially in low transmission settings.

Low practice of malaria prevention among migrants and seasonal farmworkers in Metema and west Armacheho districts, Northwest Ethiopia

Background More than hundreds and thousands of migrants and seasonal farm workers move from the highlands (relatively low malaria endemicity areas) to the lowlands (higher malaria endemicity areas) for the development of the corridor of the Amhara region during planting, weeding, and harvesting seasons in each year. Seasonal migrant workers are at high risk of malaria infection. Therefore, evidence of their knowledge level and practice in the prevention of malaria during their stay would be important. Objective The aims of this study was to assess the knowledge and practice of malaria prevention and associated factors among migrants and seasonal farm workers in Northwest Ethiopia. Method A cross-sectional study was conducted from October to November, 2018 in Metema and West Armacheho districts, northwest Ethiopia. A sample of about 950 migrants and seasonal farm workers were included using two stages of cluster sampling technique. Interview administered structured questionnaire was used. Both bi-variable and multivariable binary logistic regressions were applied to identify predictors of malaria prevention. Result The overall good knowledge of malaria (those participants who scored more than 60% of correct response for knowledge related questions) was 50.2% with 95% CI (47.0–53.0) and the overall good practice of malaria (those participants who practiced more than 60% for practice related questions) was 27.2% with 95% CI (244.3–29.9). Age (AOR = 0.51(95%CI; 0.33–0.80)), level of education (AOR = 0.55(95%CI; 0.32–0.94)), using mass media as a source of information (AOR = 2.25(95%CI; 1.52–3.32)) and length of stay at the farming site (AOR = 0.59(95%CI; 0.44–0.79)) were significantly associated with knowledge of malaria prevention. Knowledge (AOR = 6.62(95%CI; 4.46–9.83)), attitude (AOR = 2.17(95%CI1.40–3.37), use of mass media (AOR = 1.64(95%CI; 1.30–2.60)) and the length of stay (AOR = 1.93(95%CI; 1.35—2.77)) in the farming area were significantly associated with practice of malaria prevention. Conclusion The practice of malaria prevention among migrant and seasonal farm workers was low. The programmers and implementers should design tailored malaria intervention programs and strategies for these hard to reach population.

Is COVID-19 Fatality Rate Associated with Malaria Endemicity?

COVID-19 (coronavirus disease 2019) is a disease caused by the coronavirus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). COVID-19 has yielded many reported complications and unusual observations. In this article, we have reviewed one such observation: an association between malaria endemicity and reduced reported COVID-19 fatality. Malaria-endemic regions have a significantly lower reported COVID-19 fatality rate as compared to regions where malaria is non-endemic. Statistical analyses show that there is a strong negative correlation between the reported SARS-CoV-2 fatality and endemicity of malaria. In this review, we have discussed the potential role of CD-147, and potential malaria-induced immunity and polymorphisms in COVID-19 patients. Noteworthy, the results may also be due to underreported cases or due to the economic, political, and environmental differences between the malaria endemic and non-endemic countries. The study of this potential relationship might be of great help in COVID-19 therapy and prevention.

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

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.