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. 2022 Jan 18;10(2):179.
doi: 10.3390/healthcare10020179.

Disparities in Health Financing Allocation among Infectious Diseases in Ebola Virus Disease (EVD)-Affected Countries, 2005-2017

Affiliations

Disparities in Health Financing Allocation among Infectious Diseases in Ebola Virus Disease (EVD)-Affected Countries, 2005-2017

Kazuki Shimizu et al. Healthcare (Basel). .

Abstract

The Ebola virus disease (EVD) outbreaks impacted the population health due to overstretched health systems and disrupted essential health services. Despite a call to achieve equal financial allocation depending on public health needs, there has been scant examination of the fairness of investment among infectious diseases. This study analyzes the extent to which equitable development assistance for health (DAH) has been provided in accordance with disease burden in EVD-affected countries. Estimates of disability-adjusted life years (DALYs) in the Global Burden of Disease (GBD) Study 2017 and DAH Database 1990-2019 in 2005-2017 were analyzed by disease category: vaccine-preventable diseases (VPDs), HIV/AIDS, malaria, tuberculosis, and EVD. HIV/AIDS generally recorded higher ratios of DAH per DALYs (DAH/DALYs). Malaria and tuberculosis showed different trends by country, and VPDs generally presented lower ratios. In West Africa in 2013-2016, DAH/DALYs surged in EVD and fluctuated in HIV/AIDS and malaria. Tuberculosis and VPDs consistently recorded lower ratios. To achieve the risk reduction during and after health emergencies, optimal funding allocation between diseases based on the disease burden is warranted in the pre-emergency period, along with measurement of immediate health needs of populations in real-time during an emergency.

Keywords: Democratic Republic of Congo; Ebola virus disease; HIV/AIDS; West Africa; development assistance for health; health emergency; health financing; malaria; tuberculosis; vaccine-preventable diseases.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
DAH for EVD-affected countries in 2005–2017: (A) West Africa; (B) DRC.
Figure 2
Figure 2
DALYs in EVD-affected countries in 2005–2017: (A) West Africa; (B) DRC. Solid squares represent the point estimates of all-cause DALYs, and whiskers extend to the upper and lower 95% confidence intervals.
Figure 3
Figure 3
DAH/DALYs in EVD-affected countries in 2005–2017: (A) West Africa; (B) DRC. The black line represents the total DAH/DALYs, and the gray area is extended to the upper and lower 95% confidence intervals based on variations of DALYs. Colored bars represent the DAH/DALYs by disease category. Whiskers extend to the upper and lower 95% confidence intervals based on variations of DALYs. A common logarithmic scale is used on the vertical axis.
Figure 4
Figure 4
DAH/DALYs in countries in West Africa in 2005–2017: (A) Guinea; (B) Liberia; (C) Sierra Leone. The black line represents the total DAH/DALYs, and the gray area is extended to the upper and lower 95% confidence intervals based on variations of DALYs. Colored bars represent the DAH/DALYs by disease category. Whiskers extend to the upper and lower 95% confidence intervals based on variations of DALYs. A common logarithmic scale is used on the vertical axis.

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