Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model.

Reported COVID-19 cases and deaths provide a delayed and incomplete picture of SARS-CoV-2 infections in the United States (US). Accurate estimates of both the timing and magnitude of infections are needed to characterize viral transmission dynamics and better understand COVID-19 disease burden. We estimated time trends in SARS-CoV-2 transmission and other COVID-19 outcomes for every county in the US, from the first reported COVID-19 case in January 13, 2020 through January 1, 2021. To do so we employed a Bayesian modeling approach that explicitly accounts for reporting delays and variation in case ascertainment, and generates daily estimates of incident SARS-CoV-2 infections on the basis of reported COVID-19 cases and deaths. The model is freely available as the covidestim R package. Nationally, we estimated there had been 49 million symptomatic COVID-19 cases and 404,214 COVID-19 deaths by the end of 2020, and that 28% of the US population had been infected. There was county-level variability in the timing and magnitude of incidence, with local epidemiological trends differing substantially from state or regional averages, leading to large differences in the estimated proportion of the population infected by the end of 2020. Our estimates of true COVID-19 related deaths are consistent with independent estimates of excess mortality, and our estimated trends in cumulative incidence of SARS-CoV-2 infection are consistent with trends in seroprevalence estimates from available antibody testing studies. Reconstructing the underlying incidence of SARS-CoV-2 infections across US counties allows for a more granular understanding of disease trends and the potential impact of epidemiological drivers.

Relative timing of respiratory syncytial virus epidemics in summer 2021 across the United States was similar to a typical winter season.

We used a validated proxy of respiratory syncytial virus (RSV) activity in the United States (Google search data) to evaluate the onsets of RSV epidemics in 2021 and 2016-2019. Despite the unusual out-of-season summer timing, the relative timing of RSV epidemics between states in 2021 shared a similar spatial pattern with typical winter RSV seasons. Our results suggest that the onset of RSV epidemics in Florida can serve as a baseline to adjust the initiation of prophylaxis administration and clinical trials in other states regardless of the seasonality of RSV epidemics.

Rapid emergence of SARS-CoV-2 Omicron variant is associated with an infection advantage over Delta in vaccinated persons.

Background: The SARS-CoV-2 Omicron variant became a global concern due to its rapid spread and displacement of the dominant Delta variant. We hypothesized that part of Omicron's rapid rise was based on its increased ability to cause infections in persons that are vaccinated compared to Delta. Methods: We analyzed nasal swab PCR tests for samples collected between December 12 and 16, 2021, in Connecticut when the proportion of Delta and Omicron variants was relatively equal. We used the spike gene target failure (SGTF) to classify probable Delta and Omicron infections. We fitted an exponential curve to the estimated infections to determine the doubling times for each variant. We compared the test positivity rates for each variant by vaccination status, number of doses, and vaccine manufacturer. Generalized linear models were used to assess factors associated with odds of infection with each variant among persons testing positive for SARS-CoV-2. Findings: For infections with high virus copies (Ct < 30) among vaccinated persons, we found higher odds that they were infected with Omicron compared to Delta, and that the odds increased with increased number of vaccine doses. Compared to unvaccinated persons, we found significant reduction in Delta positivity rates after two (43.4%-49.1%) and three vaccine doses (81.1%), while we only found a significant reduction in Omicron positivity rates after three doses (62.3%). Conclusion: The rapid rise in Omicron infections was likely driven by Omicron's escape from vaccine-induced immunity. Funding: This work was supported by the Centers for Disease Control and Prevention (CDC).

Racial/Ethnic Segregation and Access to COVID-19 Testing: Spatial Distribution of COVID-19 Testing Sites in the Four Largest Highly Segregated Cities in the United States.

Objectives. To quantify the relationship between the segregation of Black, Indigenous, and Latinx communities and COVID-19 testing sites in populous US cities. Methods. We mapped testing sites as of June 2020 in New York City; Chicago, Illinois; Los Angeles, California; and Houston, Texas; we applied Bayesian methods to estimate the association between testing site location and the proportion of the population that is Black, Latinx, or Indigenous per block group, the smallest unit for which the US Census collects sociodemographic data. Results. In New York City, Chicago, and Houston, the expected number of testing sites decreased by 1.29%, 3.05%, and 1.06%, respectively, for each percentage point increase in the Black population. In Chicago, Houston, and Los Angeles, testing sites decreased by 5.64%, 1.95%, and 1.69%, respectively, for each percentage point increase in the Latinx population. Conclusions. In the largest highly segregated US cities, neighborhoods with more Black and Latinx residents had fewer COVID-19 testing sites, likely limiting these communities' participation in the early response to COVID-19. Public Health Implications. In light of conversations on the ethics of racial vaccine prioritization, authorities should consider structural barriers to COVID-19 control efforts. (Am J Public Health. 2022;112(3):518-526. https://doi.org/10.2105/AJPH.2021.306558).

Impact of close interpersonal contact on COVID-19 incidence: Evidence from 1 year of mobile device data.

Close contact between people is the primary route for transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). We quantified interpersonal contact at the population level using mobile device geolocation data. We computed the frequency of contact (within 6 feet) between people in Connecticut during February 2020 to January 2021 and aggregated counts of contact events by area of residence. When incorporated into a SEIR-type model of COVID-19 transmission, the contact rate accurately predicted COVID-19 cases in Connecticut towns. Contact in Connecticut explains the initial wave of infections during March to April, the drop in cases during June to August, local outbreaks during August to September, broad statewide resurgence during September to December, and decline in January 2021. The transmission model fits COVID-19 transmission dynamics better using the contact rate than other mobility metrics. Contact rate data can help guide social distancing and testing resource allocation.

Odds of Testing Positive for SARS-CoV-2 Following Receipt of 3 vs 2 Doses of the BNT162b2 mRNA Vaccine.

Importance: With the evidence of waning immunity of the mRNA vaccine BNT162b2 (Pfizer-BioNTech), a nationwide third-dose (booster) vaccination campaign was initiated in Israel during August 2021; other countries have begun to administer a booster shot as well. Objective: To evaluate the initial short-term additional benefit of a 3-dose vs a 2-dose regimen against infection of SARS-CoV-2. Design, Setting, and Participants: This preliminary retrospective case-control study used 2 complementary approaches: a test-negative design and a matched case-control design. Participants were included from the national centralized database of Maccabi Healthcare Services, an Israeli healthcare maintenance organization covering 2.5 million members. Data were collected between March 1, 2020, and October 4, 2021, and analyses focused on the period from August 1, 2021, to October 4, 2021, because the booster dose was widely administered from August 1 onward. Exposures: Either 2 doses or 3 doses of the BNT162b2 vaccine. Main Outcomes and Measures: The reduction in the odds of a positive SARS-CoV-2 polymerase chain reaction (PCR) test at different time intervals following receipt of the booster dose (0-6, 7-13, 14-20, 21-27, and 28-65 days) compared with receiving only 2 doses. Results: The study population included 306 710 members of Maccabi Healthcare Services who were 40 years and older (55% female) and received either 2 or 3 doses of the BNT162b2 vaccine and did not have a positive PCR test result for SARS-CoV-2 prior to the start of the follow-up period. During this period, there were 500 232 PCR tests performed, 227 380 among those who received 2 doses and 272 852 among those who received 3 doses, with 14 989 (6.6%) and 4941 (1.8%) positive test results in each group, respectively. Comparing those who received a booster and those who received 2 doses, there was an estimated odds ratio of 0.14 (95% CI, 0.13-0.15) 28 to 65 days following receipt of the booster (86% reduction in the odds of testing positive for SARS-CoV-2). Conclusion and Relevance: Previous studies have demonstrated that vaccine-derived protection against SARS-CoV-2 wanes over time. In this case-control analysis, we showed an association between receipt of the booster dose and a reduction in the odds of testing positive for SARS-CoV-2, potentially counteracting waning immunity in the short term. Further monitoring of data from this population is needed to determine the duration of immunity following the booster.

Maximizing the Efficiency of Active Case Finding for SARS-CoV-2 Using Bandit Algorithms.

Even as vaccination for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) expands in the United States, cases will linger among unvaccinated individuals for at least the next year, allowing the spread of the coronavirus to continue in communities across the country. Detecting these infections, particularly asymptomatic ones, is critical to stemming further transmission of the virus in the months ahead. This will require active surveillance efforts in which these undetected cases are proactively sought out rather than waiting for individuals to present to testing sites for diagnosis. However, finding these pockets of asymptomatic cases (i.e., hotspots) is akin to searching for needles in a haystack as choosing where and when to test within communities is hampered by a lack of epidemiological information to guide decision makers' allocation of these resources. Making sequential decisions with partial information is a classic problem in decision science, the explore v. exploit dilemma. Using methods-bandit algorithms-similar to those used to search for other kinds of lost or hidden objects, from downed aircraft or underground oil deposits, we can address the explore v. exploit tradeoff facing active surveillance efforts and optimize the deployment of mobile testing resources to maximize the yield of new SARS-CoV-2 diagnoses. These bandit algorithms can be implemented easily as a guide to active case finding for SARS-CoV-2. A simple Thompson sampling algorithm and an extension of it to integrate spatial correlation in the data are now embedded in a fully functional prototype of a web app to allow policymakers to use either of these algorithms to target SARS-CoV-2 testing. In this instance, potential testing locations were identified by using mobility data from UberMedia to target high-frequency venues in Columbus, Ohio, as part of a planned feasibility study of the algorithms in the field. However, it is easily adaptable to other jurisdictions, requiring only a set of candidate test locations with point-to-point distances between all locations, whether or not mobility data are integrated into decision making in choosing places to test.

The Impact of Changes in Diagnostic Testing Practices on Estimates of COVID-19 Transmission in the United States.

Estimates of the reproductive number for novel pathogens, such as severe acute respiratory syndrome coronavirus 2, are essential for understanding the potential trajectory of epidemics and the levels of intervention that are needed to bring the epidemics under control. However, most methods for estimating the basic reproductive number (R0) and time-varying effective reproductive number (Rt) assume that the fraction of cases detected and reported is constant through time. We explored the impact of secular changes in diagnostic testing and reporting on estimates of R0 and Rt using simulated data. We then compared these patterns to data on reported cases of coronavirus disease 2019 and testing practices from different states in the United States from March 4, 2020, to August 30, 2020. We found that changes in testing practices and delays in reporting can result in biased estimates of R0 and Rt. Examination of changes in the daily numbers of tests conducted and the percentages of patients who tested positive might be helpful for identifying the potential direction of bias. Changes in diagnostic testing and reporting processes should be monitored and taken into consideration when interpreting estimates of the reproductive number of coronavirus disease.

Excess Cerebrovascular Mortality in the United States During the COVID-19 Pandemic.

BACKGROUND AND PURPOSE: The magnitude and drivers of excess cerebrovascular-specific mortality during the coronavirus disease 2019 (COVID-19) pandemic are unknown. We aim to quantify excess stroke-related deaths and characterize its association with social distancing behavior and COVID-19-related vascular pathology. METHODS: United States and state-level excess cerebrovascular deaths from January to May 2020 were quantified using National Center for Health Statistic data and Poisson regression models. Excess cerebrovascular deaths were analyzed as a function of time-varying stroke-related emergency medical service (EMS) calls and cumulative COVID-19 deaths using linear regression. A state-level regression analysis was performed to determine the association between excess cerebrovascular deaths and time spent in residences, measured by Google Community Mobility Reports, during the height of the pandemic after the first COVID-19 death (February 29). RESULTS: Forty states and New York City were included. Excess cerebrovascular mortality occurred nationally from the weeks ending March 28 to May 2, 2020, up to a 7.8% increase above expected levels during the week of April 18. Decreased stroke-related EMS calls were associated with excess stroke deaths one (70 deaths per 1000 fewer EMS calls [95% CI, 20-118]) and 2 weeks (85 deaths per 1000 fewer EMS calls [95% CI, 37-133]) later. Twenty-three states and New York City experienced excess cerebrovascular mortality during the pandemic height. A 10% increase in time spent at home was associated with a 4.3% increase in stroke deaths (incidence rate ratio, 1.043 [95% CI, 1.001-1.085]) after adjusting for COVID-19 deaths. CONCLUSIONS: Excess US cerebrovascular deaths during the COVID-19 pandemic were observed and associated with decreases in stroke-related EMS calls nationally and mobility at the state level. Public health measures are needed to identify and counter the reticence to seeking medical care for acute stroke during the COVID-19 pandemic.

Measurement of SARS-CoV-2 RNA in wastewater tracks community infection dynamics.

We measured severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in primary sewage sludge in the New Haven, Connecticut, USA, metropolitan area during the Coronavirus Disease 2019 (COVID-19) outbreak in Spring 2020. SARS-CoV-2 RNA was detected throughout the more than 10-week study and, when adjusted for time lags, tracked the rise and fall of cases seen in SARS-CoV-2 clinical test results and local COVID-19 hospital admissions. Relative to these indicators, SARS-CoV-2 RNA concentrations in sludge were 0-2 d ahead of SARS-CoV-2 positive test results by date of specimen collection, 0-2 d ahead of the percentage of positive tests by date of specimen collection, 1-4 d ahead of local hospital admissions and 6-8 d ahead of SARS-CoV-2 positive test results by reporting date. Our data show the utility of viral RNA monitoring in municipal wastewater for SARS-CoV-2 infection surveillance at a population-wide level. In communities facing a delay between specimen collection and the reporting of test results, immediate wastewater results can provide considerable advance notice of infection dynamics.