Comparing frequency of booster vaccination to prevent severe COVID-19 by risk group in the United States.

There is a public health need to understand how different frequencies of COVID-19 booster vaccines may mitigate the risk of severe COVID-19, while accounting for waning of protection and differential risk by age and immune status. By analyzing United States COVID-19 surveillance and seroprevalence data in a microsimulation model, here we show that more frequent COVID-19 booster vaccination (every 6-12 months) in older age groups and the immunocompromised population would effectively reduce the burden of severe COVID-19, while frequent boosters in the younger population may only provide modest benefit against severe disease. In persons 75+ years, the model estimated that annual boosters would reduce absolute annual risk of severe COVID-19 by 199 (uncertainty interval: 183-232) cases per 100,000 persons, compared to a one-time booster vaccination. In contrast, for persons 18-49 years, the model estimated that annual boosters would reduce this risk by 14 (10-19) cases per 100,000 persons. Those with prior infection had lower benefit of more frequent boosting, and immunocompromised persons had larger benefit. Scenarios with emerging variants with immune evasion increased the benefit of more frequent variant-targeted boosters. This study underscores the benefit of considering key risk factors to inform frequency of COVID-19 booster vaccines in public health guidance and ensuring at least annual boosters in high-risk populations.

Adjusting Incidence Estimates with Laboratory Test Performances: A Pragmatic Maximum Likelihood Estimation-Based Approach.

Understanding the incidence of disease is often crucial for public policy decision-making, as observed during the COVID-19 pandemic. Estimating incidence is challenging, however, when the definition of incidence relies on tests that imperfectly measure disease, as in the case when assays with variable performance are used to detect the SARS-CoV-2 virus. To our knowledge, there are no pragmatic methods to address the bias introduced by the performance of labs in testing for the virus. In the setting of a longitudinal study, we developed a maximum likelihood estimation-based approach to estimate laboratory performance-adjusted incidence using the expectation-maximization algorithm. We constructed confidence intervals (CIs) using both bootstrapped-based and large-sample interval estimator approaches. We evaluated our methods through extensive simulation and applied them to a real-world study (TrackCOVID), where the primary goal was to determine the incidence of and risk factors for SARS-CoV-2 infection in the San Francisco Bay Area from July 2020 to March 2021. Our simulations demonstrated that our method converged rapidly with accurate estimates under a variety of scenarios. Bootstrapped-based CIs were comparable to the large-sample estimator CIs with a reasonable number of incident cases, shown via a simulation scenario based on the real TrackCOVID study. In more extreme simulated scenarios, the coverage of large-sample interval estimation outperformed the bootstrapped-based approach. Results from the application to the TrackCOVID study suggested that assuming perfect laboratory test performance can lead to an inaccurate inference of the incidence. Our flexible, pragmatic method can be extended to a variety of disease and study settings.

Programmatic Implications of National Recent HIV Infection Surveillance in Cambodia.

We compared characteristics of HIV diagnosis and recent HIV infection (ie, likely acquired within the last year) in Cambodia. We included individuals ≥ 15 years old accessing HIV testing. From August 2020 to August 2022, 53 031 people were tested for HIV, 6868 were newly diagnosed, and 192 were recently infected. We found differences in geographical burden and risk behaviors with diagnosis and recency (eg, men who have sex with men, transgender women, and entertainment workers had a nearly 2-fold increased odds of testing positive for recent infection compared to being diagnosed with HIV). Recent infection surveillance may provide unique insights into ongoing HIV acquisition to inform programs.

Preventing HIV and achieving pregnancy among HIV sero-different couples: Pilot study of a safer conception intervention in Zimbabwe.

Safer conception services are needed to minimize HIV transmission among HIV sero-different couples desiring pregnancy. Few studies have evaluated the choices couples make when offered multiple safer conception methods or real-world method acceptability and effectiveness. We piloted a comprehensive safer conception program (Clintrials.gov identifier: NCT03049176) for HIV sero-different couples planning pregnancy in Zimbabwe to measure feasibility, method uptake, acceptability, pregnancy outcome, and HIV transmission. This study was not designed to compare rates of HIV transmission by safer conception method choice but rather to understand choices couples make when seeking to minimize risk of HIV transmission and maximize likelihood of pregnancy. Couples in this prospective, non-randomized study were given a choice of one or more currently available safer conception methods: antiretroviral therapy (ART) with monthly viral load (VL) monitoring for the HIV-positive partner (ART/VL), pre-exposure prophylaxis (PrEP) for the HIV-negative partner, vaginal insemination (VI) for couples with an HIV-positive woman, and semen washing (SW) for couples with an HIV-positive man. Couples were followed monthly for up to 12 months of pregnancy attempts, quarterly during pregnancy, and 12 weeks post-partum. At each visit, data on method use, urine for pregnancy testing, and blood for HIV antibody testing, or viral load if HIV-positive, were obtained. Infants born to HIV-positive women were tested for HIV at 6 and 12 weeks. Between March 2017 and June 2019, 46 individuals from 23 HIV sero-different partnerships were enrolled and followed. At enrollment, all couples chose ART/VL, and all couples chose at least one additional method; 74% chose PrEP, 36% chose SW, and 25% chose VI. During pre-pregnancy follow-up visits, three couples discontinued SW, and one couple discontinued VI; all four of these couples opted for ART/VL plus PrEP. Satisfaction with safer conception methods was high among those who chose ART/VL and PrEP. Twelve couples achieved pregnancy. There were no cases of HIV transmission to partners, and no infants tested positive for HIV. This safer conception program is feasible and acceptable, allowing sero-different couples to safely achieve pregnancy. Sero-different couples in Zimbabwe seek a combination of HIV prevention methods, particularly ART/VL plus PrEP. Trial Registration: Clintrials.gov, NCT03049176.

Identifying Paucisymptomatic or Asymptomatic and Unrecognized Ebola Virus Disease Among Close Contacts Based on Exposure Risk Assessments and Screening Algorithms.

BACKGROUND: There is limited evidence to evaluate screening algorithms with rapid antigen testing and exposure assessments as identification strategies for paucisymptomatic or asymptomatic Ebola virus (EBOV) infection and unrecognized EBOV disease (EVD). METHODS: We used serostatus and self-reported postexposure symptoms from a cohort study to classify contact-participants as having no infection, paucisymptomatic or asymptomatic infection, or unrecognized EVD. Exposure risk was categorized as low, intermediate, or high. We created hypothetical scenarios to evaluate the World Health Organization (WHO) case definition with or without rapid diagnostic testing (RDT) or exposure assessments. RESULTS: This analysis included 990 EVD survivors and 1909 contacts, of whom 115 (6%) had paucisymptomatic or asymptomatic EBOV infection, 107 (6%) had unrecognized EVD, and 1687 (88%) were uninfected. High-risk exposures were drivers of unrecognized EVD (adjusted odds ratio, 3.5 [95% confidence interval, 2.4-4.9]). To identify contacts with unrecognized EVD who test negative by the WHO case definition, the sensitivity was 96% with RDT (95% confidence interval, 91%-99%), 87% with high-risk exposure (82%-92%), and 97% with intermediate- to high-risk exposures (93%-99%). The proportion of false-positives was 2% with RDT and 53%-93% with intermediate- and/or high-risk exposures. CONCLUSION: We demonstrated the utility and trade-offs of sequential screening algorithms with RDT or exposure risk assessments as identification strategies for contacts with unrecognized EVD.

Social Network Analysis of Ebola Virus Disease During the 2014 Outbreak in Sukudu, Sierra Leone.

Background: Transmission by unreported cases has been proposed as a reason for the 2013-2016 Ebola virus (EBOV) epidemic decline in West Africa, but studies that test this hypothesis are lacking. We examined a transmission chain within social networks in Sukudu village to assess spread and transmission burnout. Methods: Network data were collected in 2 phases: (1) serological and contact information from Ebola cases (n = 48, including unreported); and (2) interviews (n = 148), including Ebola survivors (n = 13), to identify key social interactions. Social links to the transmission chain were used to calculate cumulative incidence proportion as the number of EBOV-infected people in the network divided by total network size. Results: The sample included 148 participants and 1522 contacts, comprising 10 social networks: 3 had strong links (>50% of cases) to the transmission chain: household sharing (largely kinship), leisure time, and talking about important things (both largely non-kin). Overall cumulative incidence for these networks was 37 of 311 (12%). Unreported cases did not have higher network centrality than reported cases. Conclusions: Although this study did not find evidence that explained epidemic decline in Sukudu, it excluded potential reasons (eg, unreported cases, herd immunity) and identified 3 social interactions in EBOV transmission.

Evaluation of Severe Acute Respiratory Syndrome Coronavirus 2 Nucleocapsid Antigen in the Blood as a Diagnostic Test for Infection and Infectious Viral Shedding.

Background: SARS-CoV-2 nucleocapsid antigen can be detected in plasma, but little is known about its performance as a diagnostic test for acute SARS-CoV-2 infection or infectious viral shedding among nonhospitalized individuals. Methods: We used data generated from anterior nasal and blood samples collected in a longitudinal household cohort of SARS-CoV-2 cases and contacts. Participants were classified as true positives if polymerase chain reaction (PCR) positive for SARS-CoV-2 and as true negatives if PCR negative and seronegative. Infectious viral shedding was determined by the cytopathic effect from viral culture. Stratified by 7 days after symptom onset, we constructed receiver operating characteristic (ROC) curves to describe optimized accuracy (Youden index), optimized sensitivity, and specificity. Results: Of 80 participants, 58 (73%) were true positives while 22 (27%) were true negatives. Using the manufacturer's cutoff of 1.25 pg/mL for evaluating infection, sensitivity was higher from 0 to 7 days (77.6% [95% confidence interval {CI}, 64%-88.2%]) than from 8 to 14 days (43.2% [95% CI, 31.1%-54.5%]) after symptom onset; specificity was unchanged at 100% (95% CI, 88.1%-100%). This test had higher sensitivity (100% [95% CI, 88.4%-100%]) and lower specificity (65% [95% CI, 40.8%-84.6%]) for infectious viral shedding as compared with infection, particularly within the first week of symptom onset. Although the presence of N-antigen correlated with infectious viral shedding (r = 0.63; P < .01), sensitivity still declined over time. Additional cutoffs from ROC curves were identified to optimize sensitivity and specificity. Conclusions: We found that this SARS-CoV-2 N-antigen test was highly sensitive for detecting early but not late infectious viral shedding, making it a viable screening test for community-dwelling individuals to inform isolation practices.

Long-term consequences of food insecurity among Ebola virus disease-affected households after the 2013-2016 epidemic in rural communities of Kono District, Sierra Leone: A qualitative study.

The 2013-2016 Ebola virus disease (EVD) epidemic caused food insecurity during and immediately following local outbreaks in Sierra Leone, but longer-term effects are less well described, particularly among households with no EVD survivors. We conducted a qualitative sub-study in July 2018 in Kono District, Sierra Leone to understand the impact of food insecurity on EVD-affected households. Using data from a community-based cohort, we compiled a list of all households, within the sampled communities in Kono District, that had at least one EVD case during the epidemic. We used purposive sampling to recruit 30 households, inclusive of 10 households with no EVD survivors, to participate in the study. The research team conducted open-ended, semi-structured interviews with the head of each household. All 30 interviews were transcribed, translated, and analyzed using comparative content analysis consistent with a grounded theory approach. Most household members were facing persistent food insecurity as direct or indirect consequences of the EVD epidemic, regardless of whether they did or did not live with EVD survivors. Three major themes emerged as drivers and/or mitigators of EVD-related food insecurity. Financial instability and physical health complications were drivers of food insecurity in the population, whereas support provided by NGOs or governmental agencies was observed as a mitigator and driver of food insecurity after its removal. Among the EVD-households reporting long-term support through jobs and educational opportunities, there was sustained mitigation of food insecurity. EVD-affected households with and without survivors continue to face food insecurity three years after the EVD epidemic. Provision of support was a mitigator of food insecurity in the short term, but its removal was a driver of food insecurity in the longer term, suggesting the need for longer-term transitional support in affected households.

Infectious viral shedding of SARS-CoV-2 Delta following vaccination: A longitudinal cohort study.

The impact of vaccination on SARS-CoV-2 infectiousness is not well understood. We compared longitudinal viral shedding dynamics in unvaccinated and fully vaccinated adults. SARS-CoV-2-infected adults were enrolled within 5 days of symptom onset and nasal specimens were self-collected daily for two weeks and intermittently for an additional two weeks. SARS-CoV-2 RNA load and infectious virus were analyzed relative to symptom onset stratified by vaccination status. We tested 1080 nasal specimens from 52 unvaccinated adults enrolled in the pre-Delta period and 32 fully vaccinated adults with predominantly Delta infections. While we observed no differences by vaccination status in maximum RNA levels, maximum infectious titers and the median duration of viral RNA shedding, the rate of decay from the maximum RNA load was faster among vaccinated; maximum infectious titers and maximum RNA levels were highly correlated. Furthermore, amongst participants with infectious virus, median duration of infectious virus detection was reduced from 7.5 days (IQR: 6.0-9.0) in unvaccinated participants to 6 days (IQR: 5.0-8.0) in those vaccinated (P = 0.02). Accordingly, the odds of shedding infectious virus from days 6 to 12 post-onset were lower among vaccinated participants than unvaccinated participants (OR 0.42 95% CI 0.19-0.89). These results indicate that vaccination had reduced the probability of shedding infectious virus after 5 days from symptom onset.

All-cause and cause-specific mortality rates for Kisumu County: a comparison with Kenya, low-and middle-income countries.

BACKGROUND: Understanding the magnitude and causes of mortality at national and sub-national levels for countries is critical in facilitating evidence-based prioritization of public health response. We provide comparable cause of death data from Kisumu County, a high HIV and malaria-endemic county in Kenya, and compared them with Kenya and low-and-middle income countries (LMICs). METHODS: We analyzed data from a mortuary-based study at two of the largest hospital mortuaries in Kisumu. Mortality data through 2019 for Kenya and all LMICs were downloaded from the Global Health Data Exchange. We provided age-standardized rates for comparisons of all-cause and cause-specific mortality rates, and distribution of deaths by demographics and Global Burden of Disease (GBD) classifications. RESULTS: The all-cause age-standardized mortality rate (SMR) was significantly higher in Kisumu compared to Kenya and LMICs (1118 vs. 659 vs. 547 per 100,000 population, respectively). Among women, the all-cause SMR in Kisumu was almost twice that of Kenya and double the LMICs rate (1150 vs. 606 vs. 518 per 100,000 population respectively). Among men, the all-cause SMR in Kisumu was approximately one and a half times higher than in Kenya and nearly double that of LMICs (1089 vs. 713 vs. 574 per 100,000 population). In Kisumu and LMICs non-communicable diseases accounted for most (48.0 and 58.1% respectively) deaths, while in Kenya infectious diseases accounted for the majority (49.9%) of deaths. From age 10, mortality rates increased with age across all geographies. The age-specific mortality rate among those under 1 in Kisumu was nearly twice that of Kenya and LMICs (6058 vs. 3157 and 3485 per 100,000 population, respectively). Mortality from injuries among men was at least one and half times that of women in all geographies. CONCLUSION: There is a notable difference in the patterns of mortality rates across the three geographical areas. The double burden of mortality from GBD Group I and Group II diseases with high infant mortality in Kisumu can guide prioritization of public health interventions in the county. This study demonstrates the importance of establishing reliable vital registry systems at sub-national levels as the mortality dynamics and trends are not homogeneous.

Magnitude and Determinants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Household Transmission: A Longitudinal Cohort Study.

BACKGROUND: Households have emerged as important venues for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Little is known, however, regarding the magnitude and determinants of household transmission in increasingly vaccinated populations. METHODS: From September 2020 to January 2022, symptomatic nonhospitalized individuals with SARS-CoV-2 infection by RNA detection were identified within 5 days of symptom onset; all individuals resided with at least 1 other SARS-CoV-2-uninfected household member. These infected persons (cases) and their household members (contacts) were subsequently followed with questionnaire-based measurement and serial nasal specimen collection. The primary outcome was SARS-CoV-2 infection among contacts. RESULTS: We evaluated 42 cases and their 74 household contacts. Among the contacts, 32 (43%) became infected, of whom 5 (16%) were asymptomatic; 81% of transmissions occurred by 5 days after the case's symptom onset. From 21 unvaccinated cases, 14-day cumulative incidence of SARS-CoV-2 infection among contacts was 18/40 (45% [95% confidence interval {CI}, 29%-62%]), most of whom were unvaccinated. From 21 vaccinated cases, 14-day cumulative incidence of SARS-CoV-2 infection was 14/34 (41% [95% CI, 25%-59%]) among all contacts and 12/29 (41% [95% CI, 24%-61%]) among vaccinated contacts. At least 1 comorbid condition among cases and 10 or more days of RNA detection in cases were associated with increased risk of infection among contacts. CONCLUSIONS: Among households including individuals with symptomatic SARS-CoV-2 infection, both vaccinated-to-vaccinated and unvaccinated-to-unvaccinated transmission of SARS-CoV-2 to household contacts was common. Because vaccination alone did not notably reduce risk of infection, household contacts will need to employ additional interventions to avoid infection.

COVIDNearTerm: A simple method to forecast COVID-19 hospitalizations.

Introduction: COVID-19 has caused tremendous death and suffering since it first emerged in 2019. Soon after its emergence, models were developed to help predict the course of various disease metrics, and these models have been relied upon to help guide public health policy. Methods: Here we present a method called COVIDNearTerm to "forecast" hospitalizations in the short term, two to four weeks from the time of prediction. COVIDNearTerm is based on an autoregressive model and utilizes a parametric bootstrap approach to make predictions. It is easy to use as it requires only previous hospitalization data, and there is an open-source R package that implements the algorithm. We evaluated COVIDNearTerm on San Francisco Bay Area hospitalizations and compared it to models from the California COVID Assessment Tool (CalCAT). Results: We found that COVIDNearTerm predictions were more accurate than the CalCAT ensemble predictions for all comparisons and any CalCAT component for a majority of comparisons. For instance, at the county level our 14-day hospitalization median absolute percentage errors ranged from 16 to 36%. For those same comparisons, the CalCAT ensemble errors were between 30 and 59%. Conclusion: COVIDNearTerm is a simple and useful tool for predicting near-term COVID-19 hospitalizations.

Outdoor Activities Associated with Lower Odds of SARS-CoV-2 Acquisition: A Case-Control Study.

Access to recreational physical activities, particularly in outdoor spaces, has been a crucial outlet for physical and mental health during the COVID-19 pandemic. There is a need to understand how conducting these activities modulates the risk of SARS-CoV-2 infection. In this case-control study of unvaccinated individuals conducted in San Francisco, California, the odds of testing positive to SARS-CoV-2 were lower for those who conducted physical activity in outdoor locations (adjusted odds ratio [aOR]: 0.16, 95% confidence interval [CI]: 0.05, 0.40) in the two weeks prior to testing than for those who conducted no activity or indoor physical activity only. Individuals who visited outdoor parks, beaches, or playgrounds also had lower odds of testing positive to SARS-CoV-2 (aOR: 0.28, 95% CI: 0.11, 0.68) as compared with those who did not visit outdoor parks, beaches, or playgrounds. These findings, albeit in an unvaccinated population, offer observational data to support pre-existing ecological studies that suggest that activity in outdoor spaces lowers COVID-19 risk.

Clinical sequelae among individuals with pauci-symptomatic or asymptomatic Ebola virus infection and unrecognised Ebola virus disease in Liberia: a longitudinal cohort study.

BACKGROUND: Whether or not individuals with pauci-symptomatic or asymptomatic Ebola virus infection and unrecognised Ebola virus disease develop clinical sequelae is unknown. We assessed current symptoms and physical examination findings among individuals with pauci-symptomatic or asymptomatic infection and unrecognised Ebola virus disease compared with Ebola virus disease survivors and uninfected contacts. METHODS: Between June 17, 2015, and June 30, 2017, we studied a cohort of Ebola virus disease survivors and their contacts in Liberia. Surveys, current symptoms and physical examination findings, and serology were used to characterise disease status of reported Ebola virus disease, unrecognised Ebola virus disease, pauci-symptomatic or asymptomatic Ebola virus infection, or no infection. We pre-specified findings known to be differentially prevalent among Ebola virus disease survivors versus their contacts (urinary frequency, headache, fatigue, muscle pain, memory loss, joint pain, neurological findings, chest findings, muscle findings, joint findings, abdominal findings, and uveitis). We estimated the prevalence and incidence of selected clinical findings by disease status. FINDINGS: Our analytical cohort included 991 reported Ebola virus disease survivors and 2688 close contacts. The median time from acute Ebola virus disease onset to baseline was 317 days (IQR 271-366). Of 222 seropositive contacts, 115 had pauci-symptomatic or asymptomatic Ebola virus infection and 107 had unrecognised Ebola virus disease. At baseline, prevalent findings of joint pain, memory loss, muscle pain, and fatigue were lowest among those with pauci-symptomatic or asymptomatic infection or no infection, higher among contacts with unrecognised Ebola virus disease, and highest in reported survivors of Ebola virus disease. Joint pain was the most prevalent finding, and was reported in 434 (18%) of 2466 individuals with no infection, 14 (12%) of 115 with pauci-symptomatic or asymptomatic infection, 31 (29%) of 107 with unrecognised Ebola virus disease, and 476 (48%) of 991 with reported Ebola virus disease. In adjusted analyses, this pattern remained for joint pain and memory loss. Survivors had an increased odds of joint pain compared with unrecognised Ebola virus disease contacts (adjusted odds ratio [OR] 2·13, 95% CI 1·34-3·39); unrecognised Ebola virus disease contacts had an increased odds of joint pain compared with those with pauci-symptomatic or asymptomatic infection and uninfected contacts (adjusted OR 1·89, 95% CI 1·21-2·97). The adjusted odds of memory loss was more than four-times higher among survivors than among unrecognised Ebola virus disease contacts (adjusted OR 4·47, 95% CI 2·41-8·30) and two-times higher among unrecognised Ebola virus disease contacts than in those with pauci-symptomatic or asymptomatic infection and uninfected contacts (adjusted OR 2·05, 95% CI 1·10-3·84). By 12 months, prevalent findings had decreased in the three infected groups. INTERPRETATION: Our findings provide evidence of post-Ebola virus disease clinical sequelae among contacts with unrecognised Ebola virus disease but not in people with pauci-symptomatic or asymptomatic Ebola virus infection. FUNDING: National Cancer Institute and National Institute of Allergy and Infectious Diseases of the National Institutes of Health.

A post-outbreak assessment of exposure proximity and Ebola virus disease-related stigma among community members in Kono District, Sierra Leone: A cross-sectional study.

Background: Based on findings from other contexts, informed by intergroup contact theory, that more contact is associated with less stigma, we hypothesized that community members with greater exposure to cases of Ebola virus disease (EVD) were less likely to report EVD-related stigma towards EVD survivors. We assessed personal stigmatizing attitudes towards Ebola survivors, which reflects personal fear and judgement, as well as perceived stigma towards EVD survivors, which reflects an individual's perception of the attitudes of the community towards a stigmatized group. Methods: From September 2016 to July 2017, we conducted a cross-sectional, community-based study of EVD-related stigma among individuals who did not contract Ebola in four EVD-affected rural communities of Kono District, Sierra Leone. We identified individuals from all quarantined households and obtained a random sample of those who were unexposed. Exposed individuals either lived in a quarantined household or were reported to have been in contact with an EVD case. Our explanatory variable was proximity to an EVD case during the outbreak. Our primary outcome was stigma towards EVD survivors, measured by a 6-item adapted HIV-related stigma index validated in Zambia and South Africa, with 1 item reflecting personal stigmatizing attitudes and 5 items reflecting perceived community stigma. The 6-item EVD stigma index had good internal consistency (Cronbach's alpha=0.82). We used modified Poisson and negative binomial regression models, adjusting for potential confounders, to estimate the association between exposure proximity and EVD stigma. Results: We interviewed 538 participants aged 12 to 85 years. Most (57%) had been quarantined. Over one-third (39%) reported personal stigmatizing attitudes or perceived community stigma; the most frequently endorsed item was fear and judgment towards EVD survivors. Having contact with someone with EVD was significantly associated with a lower likelihood of perceived community stigma (prevalence ratio [PR], 0.26; 95% CI, 0.13-0.54) and personal stigmatizing attitudes (PR, 0.44; 95% CI, 0.29-0.65). In contrast, being quarantined was significantly associated with a higher likelihood of perceived community stigma (PR, 3.9; 95% CI, 1.5-10.1). Conclusions: In this cross-sectional study, we found evidence of an inverse relationship between EVD-related stigma and contact with an EVD case. This finding substantiates intergroup contact theory and may form the basis for anti-stigma interventions.

COVID-19 Vaccination and Estimated Public Health Impact in California.

Importance: Despite widespread vaccination against COVID-19 in the United States, there are limited empirical data quantifying their public health impact in the population. Objective: To estimate the number of COVID-19 cases, hospitalizations, and deaths directly averted because of COVID-19 vaccination in California. Design, Setting, and Participants: This modeling study used person-level data provided by the California Department of Public Health (CDPH) on COVID-19 cases, hospitalizations, and deaths as well as COVID-19 vaccine administration from January 1, 2020, to October 16, 2021. A statistical model was used to estimate the number of COVID-19 cases that would have occurred in the vaccine era (November 29, 2020, to October 16, 2021) in the absence of vaccination based on the ratio of the number of cases among the unvaccinated (aged <12 years) and vaccine-eligible groups (aged ≥12 years) before vaccine introduction. Vaccine-averted COVID-19 cases were estimated by finding the difference between the projected and observed number of COVID-19 cases. Averted COVID-19 hospitalizations and deaths were assessed by applying estimated hospitalization and case fatality risks to estimates of vaccine-averted COVID-19 cases. As a sensitivity analysis, a second independent model was developed to estimate the number of vaccine-averted COVID-19 outcomes by applying published data on vaccine effectiveness to data on COVID-19 vaccine administration and estimated risk of COVID-19 over time. Exposure: COVID-19 vaccination. Main Outcomes and Measures: Number of COVID-19 cases, hospitalizations, and deaths estimated to have been averted because of COVID-19 vaccination. Results: There were 4 585 248 confirmed COVID-19 cases, 240 718 hospitalizations, and 70 406 deaths in California from January 1, 2020, to October 16, 2021, during which 27 164 680 vaccine-eligible individuals aged 12 years and older were reported to have received at least 1 dose of a COVID-19 vaccine in the vaccine era (79.5% of the eligible population). The primary model estimated that COVID-19 vaccination averted 1 523 500 (95% prediction interval [PI], 976 800-2 230 800) COVID-19 cases in California, corresponding to a 72% (95% PI, 53%-91%) relative reduction in cases because of vaccination. COVID-19 vaccination was estimated to have averted 72 930 (95% PI, 53 250-99 160) hospitalizations and 19 430 (95% PI, 14 840-26 230) deaths during the study period. The alternative model identified comparable findings. Conclusions and Relevance: This study provides evidence of the public health benefit of COVID-19 vaccination in the United States and further supports the urgency for continued vaccination.

Association of Lower Exposure Risk With Paucisymptomatic/Asymptomatic Infection, Less Severe Disease, and Unrecognized Ebola Virus Disease: A Seroepidemiological Study.

Background: It remains unclear if there is a dose-dependent relationship between exposure risk to Ebola virus (EBOV) and severity of illness. Methods: From September 2016 to July 2017, we conducted a cross-sectional, community-based study of Ebola virus disease (EVD) cases and household contacts of several transmission chains in Kono District, Sierra Leone. We analyzed 154 quarantined households, comprising both reported EVD cases and their close contacts. We used epidemiological surveys and blood samples to define severity of illness as no infection, pauci-/asymptomatic infection, unrecognized EVD, reported EVD cases who survived, or reported EVD decedents. We determine seropositivity with the Filovirus Animal Nonclinical Group EBOV glycoprotein immunoglobulin G antibody test. We defined levels of exposure risk from 8 questions and considered contact with body fluid as maximum exposure risk. Results: Our analysis included 76 reported EVD cases (both decedents and survivors) and 421 close contacts. Among these contacts, 40 were seropositive (22 paucisymptomatic and 18 unrecognized EVD), accounting for 34% of the total 116 EBOV infections. Higher exposure risks were associated with having had EBOV infection (maximum risk: adjusted odds ratio [AOR], 12.1 [95% confidence interval {CI}, 5.8-25.4; trend test: P < .001) and more severe illness (maximum risk: AOR, 25.2 [95% CI, 6.2-102.4]; trend test: P < .001). Conclusions: This community-based study of EVD cases and contacts provides epidemiological evidence of a dose-dependent relationship between exposure risk and severity of illness, which may partially explain why pauci-/asymptomatic EBOV infection, less severe disease, and unrecognized EVD occurs.

Incidence and Prevalence of Coronavirus Disease 2019 Within a Healthcare Worker Cohort During the First Year of the Severe Acute Respiratory Syndrome Coronavirus 2 Pandemic.

BACKGROUND: Preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2_ infections in healthcare workers (HCWs) is critical for healthcare delivery. We aimed to estimate and characterize the prevalence and incidence of coronavirus disease 2019 (COVID-19) in a US HCW cohort and to identify risk factors associated with infection. METHODS: We conducted a longitudinal cohort study of HCWs at 3 Bay Area medical centers using serial surveys and SARS-CoV-2 viral and orthogonal serological testing, including measurement of neutralizing antibodies. We estimated baseline prevalence and cumulative incidence of COVID-19. We performed multivariable Cox proportional hazards models to estimate associations of baseline factors with incident infections and evaluated the impact of time-varying exposures on time to COVID-19 using marginal structural models. RESULTS: A total of 2435 HCWs contributed 768 person-years of follow-up time. We identified 21 of 2435 individuals with prevalent infection, resulting in a baseline prevalence of 0.86% (95% confidence interval [CI], .53%-1.32%). We identified 70 of 2414 incident infections (2.9%), yielding a cumulative incidence rate of 9.11 cases per 100 person-years (95% CI, 7.11-11.52). Community contact with a known COVID-19 case was most strongly correlated with increased hazard for infection (hazard ratio, 8.1 [95% CI, 3.8-17.5]). High-risk work-related exposures (ie, breach in protective measures) drove an association between work exposure and infection (hazard ratio, 2.5 [95% CI, 1.3-4.8). More cases were identified in HCWs when community case rates were high. CONCLUSIONS: We observed modest COVID-19 incidence despite consistent exposure at work. Community contact was strongly associated with infections, but contact at work was not unless accompanied by high-risk exposure.

Covidseeker: A Geospatial Temporal Surveillance Tool.

INTRODUCTION: Geospatial temporal data derived from smartphones traditionally used for purposes of navigation may offer valuable information for public health surveillance and locational hot spotting. Our objective was to develop a web-based application, called Covidseeker, that captures continuous fine-grained geospatial temporal data from smartphones and leverages these data to study transmission patterns of COVID-19. METHODS: This report describes the development of Covidseeker and the process by which it utilizes geospatial temporal data from smartphones and processes it into a usable format to study geospatial temporal patterns of COVID-19. We provide an overview of the design process, the principles, the software architecture, and the dashboard of the Covidseeker application and consider key challenges and strategic uses of capturing geospatial temporal data and the potential for future applications in outbreak surveillance. RESULTS: A resource such as Covidseeker can support situational awareness by providing information about the location and timing of transmission of diseases such as COVID-19. Geospatial temporal data housed in smartphones hold tremendous potential to capture more depth about where and when transmission occurs and the patterns of human mobility that lead to increases in risk of COVID-19. CONCLUSION: An enormous and highly rich source of geospatial temporal information about human mobility can be used to provide highly localized discrete information that is difficult to capture by traditional sources. The architecture of Covidseeker can be applied to help track COVID-19 and should be integrated with traditional disease surveillance practices.