Adjustable Algorithmic Tool for Assessing the Effectiveness of Maternal Respiratory Syncytial Virus (RSV) Vaccination on Infant Mortality in Developing Countries

Acute lower respiratory infection (ALRI) due to RSV is a common cause of global infant mortality, with most cases occurring in developing countries. Using data aggregated from priority countries as designated by the United States Agency for International Development’s (USAID) Maternal Child Health and Nutrition (MCHN) program, we created an adjustable algorithmic tool for visualizing the effectiveness of candidate maternal RSV vaccination on infant mortality. Country-specific estimates for disease burden and case fatality rates were computed based on established data. Country-specific RSV-ALRI incidence rates for infants 0-5 months were scaled based on the reported incidence rates for children 0-59 months. Using in-hospital mortality rates and predetermined “inflation factor,” we estimated the mortality of infants aged 0-5 months. Given implementation of a candidate maternal vaccination program, estimated reduction in infant RSV-ALRI incidence and mortality rates were calculated. User input is used to determine the coverage of the program and the efficacy of the vaccine. Using the generated algorithm, the overall reduction in infant mortality varied considerably depending on vaccine efficacy and distribution. Given a potential efficacy of 70% and a maternal distribution rate of 50% in every USAID MCHN priority country, annual RSV-ALRI-related infant mortality is estimated to be reduced by 14,862 cases. The absolute country-specific reduction is dependent on the number of live births; countries with the highest birth rates had the greatest impact on annual mortality reduction. The adjustable algorithm provides a standardized analytical tool in the evaluation of candidate maternal RSV vaccines. Ultimately, it can be used to guide public health initiatives, research funding, and policy implementation concerning the effectiveness of potential maternal RSV vaccination on reducing infant mortality

Higher rates of false-positive HIV antigen/antibody screens during the COVID-19 pandemic: implications for pregnant patients

Objective: To compare the rates of false-positive HIV 4th generation screens among pregnant patients before and during the COVID-19 pandemic. Study Design: A retrospective study evaluating the rates of false-positive HIV 4th generation screens among 44,187 pregnant patients was conducted. Pregnant patients from 3/2017-3/2019 were assigned to the “pre-COVID” cohort, and pregnant patients from 3/2020-3/2022 were assigned to the “COVID” cohort. Data including the date(s) and results of HIV 4th generation Ag/Ab combination tests and SARS-CoV-2 RT-PCR assays were ascertained via chart review. An HIV 4th generation test result was deemed “false-positive” if subsequent HIV-1/HIV-2 antibody differentiation immunoassays and/or HIV-1 nucleic acid tests were non-reactive. Results: 42/22,073 (0.19%) patients with pre-COVID pregnancies who had HIV 4th generation tests were found to have abnormal results. In comparison, 71/22,114 (0.32%) patients with pregnancies during the pandemic had abnormal test results. 16/42 (38.1%) patients with abnormal results pre-COVID had false-positive HIV screens. In comparison, 48/71 (67.6%) COVID cohort patients with abnormal results had false-positive HIV screens. Overall, the rate of false-positive HIV 4th generation tests was significantly higher in the COVID cohort compared to the pre-COVID cohort (p=0.002). Among the 48 patients with false-positive HIV screens in the COVID cohort, 13 (27.1%) had a PCR-proven COVID-19 diagnosis during pregnancy preceding their false positive result. Interestingly, 9/13 patients (69.2%) also had at least one negative HIV 4th generation screening result predating their COVID-19 diagnosis. Conclusion: Considering the maternal and neonatal implications of a positive HIV test result, OB/GYNs should be cognizant that false-positive results can occur in the setting of new/prior COVID-19 infections. Shared decision making should be used when considering the initiation of combination antiretroviral therapy, route of delivery and/or delay of breastfeeding for patients with a newly positive HIV 4th generation tests, particularly in the absence of other risk factors

Adjustable Algorithmic Tool for Assessing the Effectiveness of Maternal Respiratory Syncytial Virus (RSV) Vaccination on Infant Mortality in Developing Countries

Acute lower respiratory infection (ALRI) due to RSV is a common cause of global infant mortality, with most cases occurring in developing countries. Using data aggregated from priority countries as designated by the United States Agency for International Development’s (USAID) Maternal Child Health and Nutrition (MCHN) program, we created an adjustable algorithmic tool for visualizing the effectiveness of candidate maternal RSV vaccination on infant mortality. Country-specific estimates for disease burden and case fatality rates were computed based on established data. Country-specific RSV-ALRI incidence rates for infants 0-5 months were scaled based on the reported incidence rates for children 0-59 months. Using in-hospital mortality rates and predetermined “inflation factor,” we estimated the mortality of infants aged 0-5 months. Given implementation of a candidate maternal vaccination program, estimated reduction in infant RSV-ALRI incidence and mortality rates were calculated. User input is used to determine the coverage of the program and the efficacy of the vaccine. Using the generated algorithm, the overall reduction in infant mortality varied considerably depending on vaccine efficacy and distribution. Given a potential efficacy of 70% and a maternal distribution rate of 50% in every USAID MCHN priority country, annual RSV-ALRI-related infant mortality is estimated to be reduced by 14,862 cases. The absolute country-specific reduction is dependent on the number of live births; countries with the highest birth rates had the greatest impact on annual mortality reduction. The adjustable algorithm provides a standardized analytical tool in the evaluation of candidate maternal RSV vaccines. Ultimately, it can be used to guide public health initiatives, research funding, and policy implementation concerning the effectiveness of potential maternal RSV vaccination on reducing infant mortality