Impact of healthcare capacity disparities on the COVID-19 vaccination coverage in the United States: A cross-sectional study

BackgroundThe impact of the COVID-19 vaccination campaign in the US has been hampered by a substantial geographical heterogeneity of the vaccination coverage. Several studies have proposed vaccination hesitancy as a key driver of the vaccination uptake disparities. However, the impact of other important structural determinants such as local disparities in healthcare capacity is virtually unknown. MethodsIn this cross-sectional study, we conducted causal inference and geospatial analyses to estimate the impact of healthcare capacity on the vaccination coverage disparity in the US. We evaluated the causal relationship between the healthcare system capacity of 2,417 US counties and their COVID-19 vaccination rate. We also conducted geospatial analyses using spatial scan statistics to identify areas with low vaccination rates. FindingsWe found a positive association between the healthcare capacity of a county and vaccination uptake. We estimated that a 1% increase in the Resource-Constrained Health System Index of a county increases by 0.37% the occurrence of that county in the set of counties classified as low-vaccinated (50% vaccination rate). We also found that COVID-19 vaccinations in the US exhibit a distinct spatial structure with defined "vaccination coldspots". InterpretationWe found that the healthcare capacity of a county is an important determinant of low vaccine uptake. Our study highlights that even in high-income nations, internal disparities in healthcare capacity play an important role in the health outcomes of the nation. Therefore, strengthening the funding and infrastructure of the healthcare system, particularly in rural underserved areas, should be intensified to help vulnerable communities.

Isoniazid preventive therapy use among adult people living with HIV in Zimbabwe.

We assessed the prevalence of isoniazid preventive therapy (IPT) uptake and explored factors associated with IPT non-uptake among people living with HIV (PLHIV) using nationally representative data from the Zimbabwe Population-based HIV Impact Assessment (ZIMPHIA) 2015-2016. This was a cross-sectional study of 3418 PLHIV ZIMPHIA participants eligible for IPT, aged ≥15 years and in HIV care. Logistic regression modeling was performed to assess factors associated with self-reported IPT uptake. All analyses accounted for multistage survey design. IPT uptake among PLHIV was 12.7% (95% confidence interval (CI): 11.4-14.1). After adjusting for sex, age, rural/urban residence, TB screening at the last clinic visit, and hazardous alcohol use, rural residence was the strongest factor associated with IPT non-uptake (adjusted OR (aOR): 2.39, 95% CI: 1.82-3.12). Isoniazid preventive therapy non-uptake having significant associations with no TB screening at the last HIV care (aOR: 2.07, 95% CI: 1.54-2.78) and with hazardous alcohol use only in urban areas (aOR: 10.74, 95% CI: 3.60-32.0) might suggest suboptimal IPT eligibility screening regardless of residence, but more so in rural areas. Self-reported IPT use among PLHIV in Zimbabwe was low, 2 years after beginning national scale-up. This shows the importance of good TB screening procedures for successful IPT implementation.

Quantifying early COVID-19 outbreak transmission in South Africa and exploring vaccine efficacy scenarios

BackgroundCOVID-19 has emerged and spread at great speed globally and has presented one of the greatest public health challenges in modern times with no proven cure or vaccine. Africa is still early in this epidemic, therefore the spectrum of disease severity is not yet clear. MethodsWe used a mathematical model to fit to the observed cases of COVID-19 in South Africa to estimate the basic reproductive number and critical vaccination coverages to control the disease for different hypothetical vaccine efficacy scenarios. We also estimated the percentage reduction in effective contacts due to the social distancing measures implemented. ResultsEarly model estimates show that COVID-19 outbreak in South Africa had a basic re-productive number of 2.95 (95% credible interval [CrI] 2.83-3.33). A vaccine with 70% efficacy had the capacity to contain COVID-19 outbreak but at very higher vaccination coverage 94.44% (95% Crl 92.44-99.92%) with a vaccine of 100% efficacy requiring 66.10% (95% Crl 64.72-69.95%) coverage. Social distancing measures put in place have so far reduced the number of social contacts by 80.31% (95% Crl 79.76-80.85%). ConclusionsFindings suggest a highly efficacious vaccine would have been required to contain COVID-19 in South Africa. Therefore, the current social distancing measures to reduce contacts will remain key in controlling the infection in the absence of vaccines and other therapeutics.