On the increasing incidence of SARS-CoV- 2 in older adolescents and younger adults during the epidemic in Mexico.

OBJECTIVE: To estimate temporary changes in the inciden-ce of SARS-CoV-2-confirmed hospitalizations (by date of symptom onset) by age group during and after the national lockdown. MATERIALS AND METHODS: For each age group g, we computed the proportion E(g) of individuals in that age group among all cases aged 10-59y during the early lock-down period (April 20-May 3, 2020), and the corresponding proportion L(g) during the late lockdown (May 18-31, 2020) and post-lockdown (June 15-28, 2020) periods and computed the prevalence ratio: PR(g)=L(g)/E(g). RESULTS: For the late lockdown and post-lockdown periods, the highest PR values were found in age groups 15-19y (late: PR=1.69, 95%CI 1.05,2.72; post-lockdown: PR=2.05, 1.30,3.24) and 20-24y (late: PR=1.43, 1.10,1.86; post-lockdown: PR=1.49, 1.15,1.93). These estimates were higher in individuals 15-24y compared to those ≥30y. CONCLUSIONS: Adolescents and younger adults had an increased relative incidence of SARS-CoV-2 during late lockdown and post-lockdown periods. The role of these age groups should be considered when implementing future pandemic response efforts.

How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19.

In response to the coronavirus disease (COVID-19) pandemic, public health scientists have produced a large and rapidly expanding body of literature that aims to answer critical questions, such as the proportion of the population in a geographic area that has been infected; the transmissibility of the virus and factors associated with high infectiousness or susceptibility to infection; which groups are the most at risk of infection, morbidity and mortality; and the degree to which antibodies confer protection to re-infection. Observational studies are subject to a number of different biases, including confounding, selection bias, and measurement error, that may threaten their validity or influence the interpretation of their results. To assist in the critical evaluation of a vast body of literature and contribute to future study design, we outline and propose solutions to biases that can occur across different categories of observational studies of COVID-19. We consider potential biases that could occur in five categories of studies: (1) cross-sectional seroprevalence, (2) longitudinal seroprotection, (3) risk factor studies to inform interventions, (4) studies to estimate the secondary attack rate, and (5) studies that use secondary attack rates to make inferences about infectiousness and susceptibility.

On the Effect of Age on the Transmission of SARS-CoV-2 in Households, Schools, and the Community.

BACKGROUND: There is limited information on the effect of age on the transmission of SARS-CoV-2 infection in different settings. METHODS: We reviewed published studies/data on detection of SARS-CoV-2 infection in contacts of COVID-19 cases, serological studies, and studies of infections in schools. RESULTS: Compared to younger/middle-aged adults, susceptibility to infection for children younger than 10 years is estimated to be significantly lower, while estimated susceptibility to infection in adults older than 60 years is higher. Serological studies suggest that younger adults (particularly those younger than 35 years) often have high cumulative incidence of SARS-CoV-2 infection in the community. There is some evidence that given limited control measures, SARS-CoV-2 may spread robustly in secondary/high schools, and to a lesser degree in primary schools, with class size possibly affecting that spread. There is also evidence of more limited spread in schools when some mitigation measures are implemented. Several potential biases that may affect these studies are discussed. CONCLUSIONS: Mitigation measures should be implemented when opening schools, particularly secondary/high schools. Efforts should be undertaken to diminish mixing in younger adults, particularly individuals aged 18-35 years, to mitigate the spread of the epidemic in the community.

Temporal rise in the proportion of younger adults and older adolescents among coronavirus disease (COVID-19) cases following the introduction of physical distancing measures, Germany, March to April 2020.

Using data on coronavirus disease (COVID-19) cases in Germany from the Robert Koch Institute, we found a relative increase with time in the prevalence in 15-34 year-olds (particularly 20-24-year-olds) compared with 35-49- and 10-14-year-olds (we excluded older and younger ages because of different healthcare seeking behaviour). This suggests an elevated role for that age group in propagating the epidemic following the introduction of physical distancing measures.

Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period.

It is urgent to understand the future of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) transmission. We used estimates of seasonality, immunity, and cross-immunity for human coronavirus OC43 (HCoV-OC43) and HCoV-HKU1 using time-series data from the United States to inform a model of SARS-CoV-2 transmission. We projected that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after the initial, most severe pandemic wave. Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022. Additional interventions, including expanded critical care capacity and an effective therapeutic, would improve the success of intermittent distancing and hasten the acquisition of herd immunity. Longitudinal serological studies are urgently needed to determine the extent and duration of immunity to SARS-CoV-2. Even in the event of apparent elimination, SARS-CoV-2 surveillance should be maintained because a resurgence in contagion could be possible as late as 2024.