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Background: The coronavirus disease 2019 (COVID-19) pandemic caused severe disruptions to healthcare in many areas of the world, but data remain scarce for sub-Saharan Africa., Methods: We evaluated trends in hospital admissions and outpatient emergency department (ED) and general practitioner (GP) visits to South Africa's largest private healthcare system during 2016-2021. We fit time series models to historical data and, for March 2020-September 2021, quantified changes in encounters relative to baseline., Results: The nationwide lockdown on 27 March 2020 led to sharp reductions in care-seeking behavior that persisted for 18 months after initial declines. For example, total admissions dropped 59.6% (95% confidence interval [CI], 52.4-66.8) during home confinement and were 33.2% (95% CI, 29-37.4) below baseline in September 2021. We identified 3 waves of all-cause respiratory encounters consistent with COVID-19 activity. Intestinal infections and non-COVID-19 respiratory illnesses experienced the most pronounced declines, with some diagnoses reduced 80%, even as nonpharmaceutical interventions (NPIs) relaxed. Non-respiratory hospitalizations, including injuries and acute illnesses, were 20%-60% below baseline throughout the pandemic and exhibited strong temporal associations with NPIs and mobility. ED attendances exhibited trends similar to those for hospitalizations, while GP visits were less impacted and have returned to pre-pandemic levels., Conclusions: We found substantially reduced use of health services during the pandemic for a range of conditions unrelated to COVID-19. Persistent declines in hospitalizations and ED visits indicate that high-risk patients are still delaying seeking care, which could lead to morbidity or mortality increases in the future., (© The Author(s) 2022. Published by Oxford University Press for the Infectious Diseases Society of America.)

Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves. Population mobility is associated with SARS-CoV-2 transmission but its impacts on other respiratory viruses are not well understood. Here, the authors investigate associations between mobile phone-derived mobility metrics and the dynamics of 18 respiratory viruses in Seattle, Washington from 2018 to 2022. [ABSTRACT FROM AUTHOR]

Influenza pandemics are associated with severe morbidity, mortality, and social and economic disruption. Every summer in the United States, youths attending agricultural fairs are exposed to genetically diverse influenza A viruses (IAVs) circulating in exhibition swine, resulting in over 450 lab-confirmed zoonotic infections since 2010. Exhibition swine represent a small, defined population (-1.5% of the U.S. herd), presenting a realistic opportunity to mitigate a pandemic threat by reducing IAV transmission in the animals themselves. Through intensive surveillance and genetic sequencing of IAVs in exhibition swine in six U.S. states in 2018 (n-212), we characterized how a heterogeneous circuit of swine shows, comprising fairs with different sizes and geographic coverage, facilitates IAV transmission among exhibition swine and into humans. Specifically, we identified the role of an earlyseason national show in the propagation and spatial dissemination of a specific virus (H1-2) that becomes dominant among exhibition swine and is associated with the majority of zoonotic infections in 2018. These findings suggest that a highly targeted mitigation strategy, such as postponing swine shows for 1 to 2 weeks following the early-season national show, could potentially reduce IAV transmission in exhibition swine and spillover into humans, and this merits further study. [ABSTRACT FROM AUTHOR]

The prospect of universal influenza vaccines is generating much interest and research at the intersection of immunology, epidemiology, and viral evolution. While the current focus is on developing a vaccine that elicits a broadly cross-reactive immune response in clinical trials, there are important downstream questions about global deployment of a universal influenza vaccine that should be explored to minimize unintended consequences and maximize benefits. Here, we review and synthesize the questions most relevant to predicting the population benefits of universal influenza vaccines and discuss how existing information could be mined to begin to address these questions. We review three research topics where computational modeling could bring valuable evidence: immune imprinting, viral evolution, and transmission. We address the positive and negative consequences of imprinting, in which early childhood exposure to influenza shapes and limits immune responses to future infections via memory of conserved influenza antigens. However, the mechanisms at play, their effectiveness, breadth of protection, and the ability to "reprogram" already imprinted individuals, remains heavily debated. We describe instances of rapid influenza evolution that illustrate the plasticity of the influenza virus in the face of drug pressure and discuss how novel vaccines could introduce new selective pressures on the evolution of the virus. We examine the possible unintended consequences of broadly protective (but infection-permissive) vaccines on the dynamics of epidemic and pandemic influenza, compared to conventional vaccines that have been shown to provide herd immunity benefits. In conclusion, computational modeling offers a valuable tool to anticipate the benefits of ambitious universal influenza vaccine programs, while balancing the risks from endemic influenza strains and unpredictable pandemic viruses. Moving forward, it will be important to mine the vast amount of data generated in clinical studies of universal influenza vaccines to ensure that the benefits and consequences of these vaccine programs have been carefully modeled and explored. Author summary: There is a lot of interest in developing universal influenza vaccines that could elicit broad protection against multiple strains of influenza viruses. This impetus is generating intense basic science research in the field of influenza immunology, in the hope that new vaccine candidates can be identified, reach clinical trials, and deliver robust influenza responses. However, there are important downstream questions about using universal influenza vaccines in large populations that should be considered during the development and implementation of these novel products. Important questions include how early childhood influenza exposure limits immune responses to future influenza infections, how universal influenza vaccines could drive viral evolution, and how these new vaccines could impact the epidemiology of influenza in epidemic and pandemic seasons. Here, we synthesize the questions most relevant to predicting the population impacts of universal influenza vaccines and discuss how existing data could be analyzed to address these questions. [ABSTRACT FROM AUTHOR]