Significance This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.

The infection fatality risk (IFR) is the average number of deaths per infection by a pathogen and is key to characterizing the severity of infection across the population and for specific demographic groups. To date, there are few empirical estimates of IFR published due to challenges in measuring infection rates.1,2 Outside of closed, closely surveilled populations where infection rates can be monitored through viral surveillance, we must rely on indirect measures of infection, like specific antibodies. Representative seroprevalence studies provide an important avenue for estimating the number of infections in a community, and when combined with death counts can lead to robust estimates of the IFR. We estimated overall and age-specific IFR for the canton of Geneva, Switzerland using age-stratified daily case and death incidence reports combined with five weekly population-based seroprevalence estimates.3 From February 24th to June 2nd there were 5’039 confirmed cases and 286 reported deaths within Geneva (population of 506’765). We inferred age-stratified (5-9, 10-19, 20-49, 50-65 and 65+) IFRs by linking the observed number of deaths to the estimated number of infected individuals from each serosurvey. We account for the delays between infection and seroconversion as well as between infection and death.4 Inference is drawn in a Bayesian framework that incorporates uncertainty in seroprevalence estimates (supplement).Of the 286 reported deaths caused by SARS-CoV-2, the youngest person to die was 31 years old. Infected individuals younger than 50 years experienced statistically similar IFRs (range 0.00032-0.0016%), which increases to 0.14% (95% CrI 0.096-0.19) for those 50-64 years old to 5.6% (95% CrI 4.3-7.4) for those 65 years and older (supplement). After accounting for demography and age-specific seroprevalence, we estimate a population-wide IFR of 0.64% (95% CrI 0.38-0.98).Our results are subject to two notable limitations. Among the 65+ age group that died of COVID-19 within Geneva, 50% were reported among residents of assisted care facilities, where around 0.8% of the Geneva population resides. While the serosurvey protocol did not explicitly exclude these individuals, they are likely to have been under-represented. This would lead to an overestimation of the IFR in the 65+ age group if seroprevalence in this institutionalized population was higher than in the general population (supplement). Further, our IFR estimates are based on current evidence regarding post-infection antibody kinetics, which may differ between severe and mild infections. If mild infections have significantly lower and short-lived antibody responses, our estimates of IFR may be biased upwards.5Estimates of IFR are key for understanding the true pandemic burden and for weighing different risk reduction strategies. The IFR is not solely determined by host and pathogen biology, but also by the capacity of health systems to treat severe cases. Despite having among the highest per capita incidence in Switzerland, Geneva’s health system accommodated the influx of cases needing intensive care (peak of 80/110 ICU-beds including surge capacity) while maintaining care quality standards. As such, our IFR estimates can be seen as a best-case scenario with respect to health system capacity. Our results reveal that population-wide estimates of IFR mask great heterogeneity by age and point towards the importance of age-targeted interventions to reduce exposures among those at highest risk of death.

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Background Cholera was introduced into Haiti in 2010. Since then, more than 820 000 cases and nearly 10 000 deaths have been reported. Oral cholera vaccine (OCV) is safe and effective, but has not been seen as a primary tool for cholera elimination due to a limited period of protection and constrained supplies. Regionally, epidemic cholera is contained to the island of Hispaniola, and the lowest numbers of cases since the epidemic began were reported in 2019. Hence, Haiti may represent a unique opportunity to eliminate cholera with OCV. Methods In this modelling study, we assessed the probability of elimination, time to elimination, and percentage of cases averted with OCV campaign scenarios in Haiti through simulations from four modelling teams. For a 10-year period from January 19, 2019, to Jan 13, 2029, we compared a no vaccination scenario with five OCV campaign scenarios that differed in geographical scope, coverage, and rollout duration. Teams used weekly department-level reports of suspected cholera cases from the Haiti Ministry of Public Health and Population to calibrate the models and used common vaccine-related assumptions, but other model features were determined independently. Findings Among campaigns with the same vaccination coverage (70% fully vaccinated), the median probability of elimination after 5 years was 0-18% for no vaccination, 0-33% for 2-year campaigns focused in the two departments with the highest historical incidence, 0-72% for three-department campaigns, and 35-100% for nationwide campaigns. Two-department campaigns averted a median of 12-58% of infections, three-department campaigns averted 29-80% of infections, and national campaigns averted 58-95% of infections. Extending the national campaign to a 5-year rollout (compared to a 2-year rollout), reduced the probability of elimination to 0-95% and the proportion of cases averted to 37-86%. Interpretation Models suggest that the probability of achieving zero transmission of Vibrio cholerae in Haiti with current methods of control is low, and that bolder action is needed to promote elimination of cholera from the region. Large-scale cholera vaccination campaigns in Haiti would offer the opportunity to synchronise nationwide immunity, providing near-term population protection while improvements to water and sanitation promote long-term cholera elimination.

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We report about field and theoretical studies on the ecology of the aquatic snails (Bulinus spp. and Biomphalaria pfeifferi) that serve as obligate intermediate hosts in the complex life cycle of the parasites causing human schistosomiasis. Snail abundance fosters disease transmission, and thus the dynamics of snail populations are critically important for schistosomiasis modeling and control. Here, we single out hydrological drivers and density dependence (or lack of it) of ecological growth rates of local snail populations by contrasting novel ecological and environmental data with various models of host demography. Specifically, we study various natural and manmade habitats across Burkina Faso's highly seasonal climatic zones. Demographic models are ranked through formal model comparison and structural risk minimization. The latter allows us to evaluate the suitability of population models while clarifying the relevant covariates that explain empirical observations of snail abundance under the actual climatic forcings experienced by the various field sites. Our results link quantitatively hydrological drivers to distinct population dynamics through specific density feedbacks, and show that statistical methods based on model averaging provide reliable snail abundance projections. The consistency of our ranking results suggests the use of ad hoc models of snail demography depending on habitat type (e.g., natural vs. man-made) and hydrological characteristics (e.g., ephemeral vs. permanent). Implications for risk mapping and space-time allocation of control measures in schistosomiasisendemic contexts are discussed.freshwater snails | water-based disease | infection controls | environmental monitoring

Understanding the risk of infection from household- and community-exposures and the transmissibility of asymptomatic infections is critical to SARS-CoV-2 control. Limited previous evidence is based primarily on virologic testing, which disproportionately misses mild and asymptomatic infections. Serologic measures are more likely to capture all previously infected individuals. We apply household transmission models to data from a cross-sectional, household-based population serosurvey of 4,534 people ≥5 years from 2,267 households enrolled April-June 2020 in Geneva, Switzerland. We found that the risk of infection from exposure to a single infected household member aged ≥5 years (17.3%,13.7-21.7) was more than three-times that of extra-household exposures over the first pandemic wave (5.1%,4.5-5.8). Young children had a lower risk of infection from household members. Working-age adults had the highest extra-household infection risk. Seropositive asymptomatic household members had 69.4% lower odds (95%CrI,31.8-88.8%) of infecting another household member compared to those reporting symptoms, accounting for 14.5% (95%CrI, 7.2-22.7%) of all household infections.