A confounding factor (third variable) may mask an actual association or falsely demonstrate an apparent association between the study variables where no real association exists. If confounding factors are not measured and considered, bias may result in the conclusion of the stud. Confounding occurs when a measure designed to assess a particular construct inadvertently measures something else as well. 
The confounding factor can interfere with the real effect. For this reason, the etiological importance of a variable needs to be prevented or removed as much as possible. Confounding may be prevented by the use of randomization, restriction, or matching. The term restriction is used when a researcher chooses only one variation of a participant to restrict the possibility of including a confounding variable. As far as malaria is a possible confounding factor suggested to create a cross heterogeneous effect towards COX-Cov2, We designed this study to exclude this factor by restricting the study sample to malaria-free countries. Literature raised the question of unknown contribution factors regarding COVID-19 mortality variances. Some of the literature raised the possibility of malaria as one factor in explaining the variances in COVID-19 mortalities.13,15,16,17 ,18 , 19,20 . One of these studies found that malaria has an added effect on TB prevalence effect in decreasing the COVID-19 deaths in malaria-endemic areas. 19 Countries are classified as either malaria-free or malaria-endemic countries. All malaria-free countries have a certain TB prevalence. In general, countries might be classified as low, intermediate, and high TB incidence countries. Malaria endemic countries are usually highly endemic in TB., This might lead to confounding when testing relation of TB or malaria against COVID-19 mortality.
Previous studies testing TB influence on COVID-19 mortality fail to control this factor.
In this study by using Kendall’s-τ correlation coefficient test, there was a high reverse-directional significant correlation between COVID-19 mortality rates and TB prevalence (in absence of suggested confounded factor of malaria endemicity) with a reported p- value (0.008) (table 1).
Kendall’s τ has been classically used to test the significance of cross-correlation between two variables when their distributions significantly deviate from the normal distribution. In that case, a significance test based on the distribution-free τ, which is a function of the ranks of the variates rather than their actual values, offers more power than other parametric tests.
The finding in this study of TB prevalence influence on COVID-19 mortality in malaria-free countries is strongly in agreement with a previous study in malaria-endemic countries.19 Furthermore, it consolidates other studies on the relation of LTB to covid-19 mortality.10,11,12,,13 ,14, .
A second test conducted in this study was the Kruskal-Wallis Test. It is a non-parametric method used for testing whether samples originate from the same distribution or not by determining whether the medians of two or more groups are different., It was conducted among different TB prevalence groups. It showed that the Chi-Square result equals 7.740 with P-value equals 0.021 (S)These results signify that there are differences among the groups, but as Kruskal-Wallis Test is an omnibus test statistic and doesn’t tell which group is different from other groups. It is used for comparing two or more independent samples of equal or different sample sizes. The Kruskal–Wallis test is a rank-based test that is similar to the Mann–Whitney U test but can be applied to one-way data with more than two groups. It is a non-parametric alternative to the one-way ANOVA test, which extends the two-samples Wilcoxon test.
However, like most non-parametric tests, the Kruskal-Wallis test is not as powerful as the ANOVA but, assumptions of one-way ANOVA are not met in our sample.
A Mann-Whitney U test (another non-parametric test) was used to compare the differences between two independent samples as far as the sample distributions are not normally distributed as shown before.
It showed that the low TB prevalent group when tested against groups moderately TB prevalent and highly prevalent group show significant association with decreased mortality from covid-19 (table 2).
The non-significant association between moderate and high TB prevalent groups (table 2) needs further consideration. The test fails to find a significant association due to possible existing confounding factors. A possible one is the malaria elimination date since faster progress was achieved in malaria elimination recently, compared to TB control in many countries. According to WHO, the malaria elimination net is widening. Furthermore, more countries are moving towards zero indigenous cases: The number of countries with fewer than 100 indigenous cases was 17, 25, and 27 in 2010, 2017, and,2018 respectively, which is a strong indicator that elimination is within reach. .
Despite other significant associations, some countries are disparate fatality rates / M inhabitants among low TB prevalence countries. Also, a disparity exists in fatality rates among high TB prevalence countries. We suggest other possible confounding factors in addition to malaria residual immunity already mentioned which include but are not restricted to BCG policy of country and BCG coverage, other mycobacterial cross-reaction or effects by other vaccines population size measures taken, habits, some LAVs which have induced a broad, nonspecific, protection against unrelated pathogens and decreased mortality from conditions other than the targeted infectious diseases. . Furthermore, this study was done without any regard for income, healthcare facilities.
Controlled clinical studies need to be conducted before further considering reviewing global strategies for the prevention and treatment of TB and malaria. According to global strategy in the treatment of TB, the main goal is to treat the active cases in areas with a high incidence of TB, but in areas with a low incidence of TB, the goal also includes prophylactic treatment for LTBI
Whoever, in recent years, studies have gradually narrowed down to the preventive treatment of LTBI for high-risk target groups. Targeted TB testing and treatment programs in USA and many European countries conducted among high-risk groups.,. It was questionable that chasing after LTB infection treatment a time before.If prophylaxis is provided for all LTBI patients, it will result in an enormous waste of resources and increase the likelihood of anti-TB drug resistance.33 Added to that we raised the possible role of LTB on decreasing COVID-19 mortality.
TB prevalence in this study was taken as the highest available figure for up to 10 years ago (since 2011 outward) as far as the immunity created by latent or active TB infection last for a long time. The major dilemma is that there is no test to assure that every person diagnosed with an immune reaction to LTB treatment can be guaranteed free from the active form of infection, although it has been agreed that reactivation is unlikely after 2 years.
We considered 10 years the least time for immune-reaction to wane as far as it is well known that a related Mycobacterium which is Mycobacterium Bovis ( BCG ), waned by at least by 10 years.. A longer time for immune reaction time after natural infection is possible, but the exact time for waning such immunity is unknown yet.