Global Health Security Index not a proven surrogate for health systems capacity to respond to pandemics: The case of COVID-19.

INTRODUCTION: Global Health Security borders on prevention, detection and response to public health threats like the novel coronavirus disease 2019 (COVID-19). Global Health Security Index (GHSI) of 2019 and 2021 revealed the world remains ill-prepared to deal with future pandemics, evident in the historic impact of COVID-19 on countries. As at 7th December 2022, COVID-19 has infected over 600 million people and claimed over six million lives, mostly in countries with higher GHSI scores. OBJECTIVE: Determine whether the GHSI scores of countries have a correlation with COVID-19 cases, deaths and vaccination coverage, while adjusting for country level dynamics. METHODS: This paper utilizes GHSI database of 195 countries. Data consists of 171 questions grouped into 37 indicators across six overarching categories on health security and COVID-19. Multivariate multiple regression analysis with robust standard errors was conducted to test the hypothesis that high GHSI ratings do not guarantee better COVID-19 outcomes like cases, deaths and vaccination coverage. Also, avplots STATA command was used to check outliers with potential negative effect on outcome and predictor variables. RESULTS: Global average GHSI score for all 195 countries was 38.9. United States of America recorded the highest GHSI score of 75.9 but also recorded one of the highest COVID-19 cases and deaths; Somalia recorded the worst GHSI score of 16.0 and one of the lowest COVID-19 cases and deaths. High GHSI scores did not associate positively with reduction in COVID-19 cases (Coef=157133.4, p-value=0.009, [95%CI 39728.64 274538.15]) and deaths (Coef=1405.804, p-value=0.047, [95%CI 18.1 2793.508]). However, high GHSI ratings associated with increases in persons fully vaccinated per 100 population (Coef=0.572, p-value=0.000, [95%CI.272.873]). CONCLUSION: It appears the world might still not be adequately prepared for the next major pandemic, if the narrative remains unchanged. Countries that recorded higher GHSI scores, counter-intuitively, recorded higher COVID-19 cases and deaths. Countries need to invest more in interventions towards attaining Universal Health Coverage (UHC) including integrated health systems and formidable primary health care to enhance preparedness and response to pandemics.

Prevalence, progress, and social inequalities of home deliveries in Ghana from 2006 to 2018: insights from the multiple indicator cluster surveys.

BACKGROUND: Delivery in unsafe and unsupervised conditions is common in developing countries including Ghana. Over the years, the Government of Ghana has attempted to improve maternal and child healthcare services including the reduction of home deliveries through programs such as fee waiver for delivery in 2003, abolishment of delivery care cost in 2005, and the introduction of the National Health Insurance Scheme in 2005. Though these efforts have yielded some results, home delivery is still an issue of great concern in Ghana. Therefore, the aim of the present study was to identify the risk factors that are consistently associated with home deliveries in Ghana between 2006 and 2017-18. METHODS: The study relied on datasets from three waves (2006, 2011, and 2017-18) of the Ghana Multiple Indicator Cluster surveys (GMICS). Summary statistics were used to describe the sample. The survey design of the GMICS was accounted for using the 'svyset' command in STATA-14 before the association tests. Robust Poisson regression was used to estimate the relationship between sociodemographic factors and home deliveries in Ghana in both bivariate and multivariable models. RESULTS: The proportion of women who give birth at home during the period under consideration has decreased. The proportion of home deliveries has reduced from 50.56% in 2006 to 21.37% in 2017-18. In the multivariable model, women who had less than eight antenatal care visits, as well as those who dwelt in households with decreasing wealth, rural areas of residence, were consistently at risk of delivering in the home throughout the three data waves. Residing in the Upper East region was associated with a lower likelihood of delivering at home. CONCLUSION: Policies should target the at-risk-women to achieve complete reduction in home deliveries. Access to facility-based deliveries should be expanded to ensure that the expansion measures are pro-poor, pro-rural, and pro-uneducated. Innovative measures such as mobile antenatal care programs should be organized in every community in the population segments that were consistently choosing home deliveries over facility-based deliveries.