The infectious diseases are predominantly among poor populations living in low-income countries, most of them are treatable with existing medicines or preventable in the first place, among these diseases are including Tuberculosis within HIV/AIDS-negative, Malaria, leprosy, and other neglected diseases [1, 2]. The main problem of the low-income countries is to access to the necessary medicines which remain an intractable political and economic problem, where their population is the poorest socio-economic clusters that strangely suffer from a lack of access to existing medicines [3, 4]. These socio-economics problems persist in East African countries since all countries’ budget are spent on projects and priorities that do not relate with the basic needs and demands of their populations (military, education). This factor is not explained by these government, therefore, it would be better to show the contribution of socio-economics of East African countries by assuming this economic factor as gross national income (GNI) to protect their citizens.
In this study, we investigate the evolution between East African countries in the eradicating process of infectious diseases’ mortalities relied on the effect of gross national income (GNI) increment, meanwhile the majority of the countries participating share common problems as socio-economics, and also all are developing countries, their income growth could contribute to that evolution of eradicating mortalities in several sectors. Moreover, it was the factor that gross national income compared first among participant countries, as enclosed in the target of SDGs and MDGs on each country for mortalities reduction, since infectious diseases highlighted to be an issue to concern, mostly TB, Malaria, and HIV/AIDS [36, 37]. The socio-economic problem underlined to be the main roots of mortalities among the risked patients in underdeveloped and developing countries, especially for the poor farms living with poor management of their livestock production, engaging in hard forces that lead to high TB prevalence in 2017 among participant countries [13, 15-18, 46].
TB among HIV-negative, Malaria, leprosy and neonates protected against tetanus data were mined in WHO database since they are the most prevalent in recent years and compared with GNI for showing the difference in evolution process of mortalities reduction instigated by infectious diseases in East African countries (Burundi, Uganda, Rwanda, Kenya, Tanzania, and DRC). The privileged data were recorded from 2004 until 2015. The persistence and occurrence of new cases from long-standing and new infectious diseases, besides some transported among all participant countries like TB among HIV-negative and Malaria [13, 14] become frequently issues to investigate. Moreover, leprosy is national diseases although there are no recent studies showed its prevalence among participant countries except Global Leprosy Strategy 2016–2020 named Accelerating towards a leprosy-free world was based on strengthening government ownership to stop leprosy and its complication . Our study is the first to describe the significant effect of GNI to the evolution of mortalities caused by infectious diseases through the following hypothesis: Ho: The all means different is not significant and the alternative is that means different is significant at the 0.05 level, and Levene’s and Brown-Forsythe test for homogeneity for variances. With regards to the comparative analysis of new cases and deaths between participant countries, the box-charts showed that there is a different in full ranges of variation in either minimum, maximum, quartiles or medians.
The mean differences between countries in new cases and deaths
The Levene’s and Brown-Forsythe test showed that the new cases recorded on leprosy up to 2015 are almost the same in four countries (Uganda, Rwanda, Kenya, and Burundi) and quite different in DRC and Tanzania. This results would be compared with the update report of leprosy since it showed the increment of the recorded number for some countries (Uganda, Tanzania, and DRC) and decrement in Rwanda, unfortunately, some countries did not show their reports (Burundi and Kenya) . The mortalities caused by Malaria are differently in five countries compared between them except comparisons with DRC, new cases of Malaria are different in four countries in comparisons (Tanzania, Tanzania, Rwanda, and Uganda) while all others are almost equal. These results were similar with WHO Malaria report 2015, as it showed that Burundi, DRC, and Uganda new cases and deaths were inclined while Rwanda, Kenya, and Tanzania were declined up to zero . The different in mortalities caused by TB among HIV/AIDS-negative is almost equal in the comparison within four countries (Tanzania, Kenya, and Rwanda) and different in other countries. The different in neonates protected at birth against neonatal tetanus was almost equal in some countries and different in others.
The relationship and effect of GNI and all responses
The increasing GNI had contributed positively in all countries in the reduction of new cases of leprosy since the relationship is in a negative direction with GNI, the effect was positive on Mortalities caused by Malaria because the relationship was negative in Rwanda, Tanzania and Kenya, weak in Uganda while there was no effect in Burundi and DRC since the relationship is positive, unfortunately, there was no contribution of GNI on new cases of Malaria is since the relationship was both strong and positive in five countries excluding Tanzania which had a weak relationship. This result is slightly similar with WHO report 2015 but different for some output . The effect of GNI was almost useless in all countries because the relationship with mortalities caused by TB was both strong and positive in DRC and Uganda. This result was closer with the WHO report 2018 that classify some countries in high TB burden. There was no clear effect of GNI in neonates protected at birth against neonatal tetanus since the relationship of Neonates protected at birth against neonatal tetanus with GNI is weak in Uganda and Kenya and strongly positive in others countries. Generally, there was no effect of GNI in the evolution of eradicating mortalities caused by infectious diseases with respect to time. The results of this study are similar to the highlighted causes of the study showed how some Low-income countries spent budget on unrelated projects rather than the healthcare of their citizens .
Our study has obvious limitation including excluded countries in the comparative due to there are no recorded data in several years, and missing value detection is not possible to manage, other infectious diseases even either new or current that do not have the recorded data, the relationship between GNI and others responses are generalized due to the sampling are not from the population. However, further study can be addressed on the persistence of the treatable and preventable infectious diseases in the most risked countries by considering the household surveys for obtaining update information.