RESUMEN
BACKGROUND: Uncertainties surrounding the 2019 novel coronavirus (COVID-19) remain a major global health challenge and requires attention. Researchers and medical experts have made remarkable efforts to reduce the number of cases and prevent future outbreaks through vaccines and other measures. However, there is little evidence on how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection entropy can be applied in predicting the possible number of infections and deaths. In addition, more studies on how the COVID-19 infection density contributes to the rise in infections are needed. This study demonstrates how the SARS-COV-2 daily infection entropy can be applied in predicting the number of infections within a given period. In addition, the infection density within a given population attributes to an increase in the number of COVID-19 cases and, consequently, the new variants. RESULTS: Using the COVID-19 initial data reported by Johns Hopkins University, World Health Organization (WHO) and Global Initiative on Sharing All Influenza Data (GISAID), the result shows that the original SAR-COV-2 strain has R0<1 with an initial infection growth rate entropy of 9.11 bits for the United States (U.S.). At close proximity, the average infection time for an infected individual to infect others within a susceptible population is approximately 7 minutes. Assuming no vaccines were available, in the U.S., the number of infections could range between 41,220,199 and 82,440,398 in late March 2022 with approximately, 1,211,036 deaths. However, with the available vaccines, nearly 48 Million COVID-19 cases and 706, 437 deaths have been prevented. CONCLUSION: The proposed technique will contribute to the ongoing investigation of the COVID-19 pandemic and a blueprint to address the uncertainties surrounding the pandemic.
Asunto(s)
COVID-19 , COVID-19/epidemiología , COVID-19/prevención & control , Brotes de Enfermedades , Salud Global , Humanos , Pandemias/prevención & control , SARS-CoV-2 , Estados Unidos/epidemiologíaRESUMEN
INTRODUCTION: Sub-Saharan Africa houses over two-thirds of the 37 million people living with human immunodeficiency virus (HIV) globally and of this, 5-20% are co-infected with Hepatitis B virus (HBV). This is double jeopardy, especially for women of reproductive age in these settings, who can transmit both viruses vertically as well as horizontally to their children. The objectives of this study were to investigate the prevalence and determinants of HBV among women of reproductive age living with HIV. METHODS: This was a cross-sectional study of HIV-infected women of reproductive age in Benue State, Nigeria. Participants were eligible for the study if they were HIV-infected women (ages 18-45 years) receiving care from any of the selected study sites. A global rapid hepatitis B surface antigen (HBsAg) antibody test strip was used to test for HBsAg in plasma. A pretested questionnaire was used to collect data on sociodemographic, clinical and lifestyle characteristics of participants. We estimated prevalence of HBV infection and used multivariable logistic regression to determine factors associated with the infection at a significance level of <0.05. RESULTS: A total of 6577 women were screened for HBsAg. The prevalence of HBV was 10.3% (95% CI: 9.5-10.9%). Age, parity and male partner's HIV status were found to be associated with having HBV infection. Compared to women older than 40 years, the odds of HBV infection increased significantly with increasing age until age 35 years and decreased significantly with increasing parity (versus no parity). Women with HIV-infected partners and those without a partner had higher odds of HBV infection compared to women with HIV-negative partners. CONCLUSION: HBV is hyperendemic among HIV-infected women of reproductive age in North Central Nigeria. Specific programs targeting HBV testing, vaccination and treatment of all women of reproductive age need to be developed in this resource-limited, high-need setting.