Surveillance of SARS-CoV-2 through reported positive RT-PCR tests is biased due to non-random testing. Prevalence estimation in population-based samples corrects for this bias. Within this context, the pooled testing design offers many advantages, but several challenges remain with regards to the analysis of such data. We developed a Bayesian model aimed at estimating the prevalence of infection from repeated pooled testing data while (i) correcting for test sensitivity; (ii) propagating the uncertainty in test sensitivity; and (iii) including correlation over time and space. We validated the model in simulated scenarios, showing that the model is reliable when the sample size is at least 500, the pool size below 20, and the true prevalence below 5%. We applied the model to 1.49 million pooled tests collected in Switzerland in 2021–2022 in schools, care centres, and workplaces. We identified similar dynamics in all three settings, with prevalence peaking at 4–5% during winter 2022. We also identified differences across regions. Prevalence estimates in schools were correlated with reported cases, hospitalizations, and deaths (coefficient 0.84 to 0.90). We conclude that in many practical situations, the pooled test design is a reliable and affordable alternative for the surveillance of SARS-CoV-2 and other viruses.

Samples of the bones of 47 individuals from 46 Czech and Moravian ossuaries were dated by the 14C method and analyzed for the collagen isotopic composition of carbon (δ13C) and nitrogen (δ15N). Most of the data for the ages of the remains corresponded to the cooler and damper periods described over the past 1000 years. Of the studied samples, the greatest number of remains corresponded to the Spörer (1400–1570), Dalton (1790–1830) and Wolf minima (1280–1350). One sample studied falls within the Maunder minimum (1645–1715). It can be assumed that these minima are connected with a reduced production of food and fodder, that may have initiated famines, epidemics and armed conflicts. Individual climatic minima showed positive correlations between δ13C and δ15N values, indicating that the individuals studied consumed complementary plant or animal diets to different degrees. The elevated δ15N values in our studied samples compared to the skeletal compositions of the population of the La Tène period (380 – 150 BC) and Germanic inhabitants in the territory of Bohemia (5th–6th centuries AD) and Great Moravia (9th–early 10th centuries AD) might reflect the effect of greater consumption of animal proteins or the proteins of omnivorous animals and fish, which compensated for the lack of plant foodstuffs during the colder periods.

The isotopic composition of carbon and nitrogen of the bone collagen for the Spörer and Dalton minima differs from the Wolf minimum. The younger minima show higher δ15N values for a given δ13C value.

This paper investigates the events and lessons from the 1848–49 cholera epidemic in Hungary. For contemporaries, the ongoing revolution and civil war pushed the devastation of the cholera epidemic into the background, even though the death rate was similar to that of the earlier 1831 infection. The epidemic hit the country in a period when the revolutionary Hungarian state was waging a war of self-defense. This article strives to refute the historiographic view that the movements of the different armies had a considerable influence on the development of the epidemic. Instead, this article argues that the cholera epidemic was a demographic crisis unfolding in the background of war, but for the most part independently of it. It mattered that most people of that time had already directly experienced cholera and that the Hungarian government did not want to cause panic with restrictive measures. In 1848, cholera was not a “mobilizing factor,” but in 1849 it contributed to the demoralization of the hinterland and frequently appeared in the political propaganda of the civil war.

Introduction of African swine fever (ASF) to China in mid-2018 and the subsequent transboundary spread across Asia devastated regional swine production, affecting live pig and pork product-related markets worldwide. To explore the spatiotemporal spread of ASF in China, we reconstructed possible ASF transmission networks using nearest neighbour, exponential function, equal probability, and spatiotemporal case-distribution algorithms. From these networks, we estimated the reproduction numbers, serial intervals, and transmission distances of the outbreak. The mean serial interval between paired units was around 29 days for all algorithms, while the mean transmission distance ranged 332 –456 km. The reproduction numbers for each algorithm peaked during the first two weeks and steadily declined through the end of 2018 before hovering around the epidemic threshold value of 1 with sporadic increases during 2019. These results suggest that 1) swine husbandry practices and production systems that lend themselves to long-range transmission drove ASF spread; 2) outbreaks went undetected by the surveillance system. Efforts by China and other affected countries to control ASF within their jurisdictions may be aided by the reconstructed spatiotemporal model. Continued support for strict implementation of biosecurity standards and improvements to ASF surveillance is essential for halting transmission in China and spread across Asia.

This article provides a narrative about archival research experience in Sierra Leone as the coronavirus outbreak spread globally in early 2020. Coincidentally, the research concerned the country’s history of epidemics since 1787, when Freetown, its first city, accommodated freed Blacks repatriated from Britain and the Americas. As Sierra Leone prepared for another disease outbreak after Ebola in 2014, leaving or staying in Freetown (after seven months into a ten-month Fulbright US Scholar term) had health and research outcomes at stake. Historicizing the pandemic while engaging personal/social memory in historical accounts, the article highlights containment measures adopted against epidemics/pandemics across time.

Historical research on urban epidemics has focused on the interaction of diseases with social and spatial gradients, such as class, ethnicity, or neighborhood. Even sophisticated historical studies usually lack data on health-related behavior or health-related perceptions, which modern analysts tend to emphasize. With detailed source material from the Finnish city of Tampere during a typhoid epidemic in 1916, we are able to combine both dimensions and look at how material and social constraints interacted with behavior and knowledge to produce unequal outcomes. We use data on socioeconomic status, location, and physical habitat as well as the self-reported behavior and expressed understandings of transmission mechanisms of the infected people to identify the determinants of some falling ill earlier or later than others. Applying survival analysis to approximately 2,500 cases, we show that disease avoidance behavior was deficient and constrained by physical habitat, regardless of considerable public health campaigning. Behavioral guidelines issued by authorities were sub-optimally communicated, unrealistic, and inadequately followed. Boiling water was hampered by shared kitchens, and access to laundry houses for additional hygiene was uneven. Centralized chemical water purification finally leveled the playing field by socializing the cost of prevention and eliminating key sources of unequal risk.

We examined the association between face masks and risk of infection with SARS-CoV-2 using cross-sectional data from 3,209 participants in a randomized trial exploring the effectiveness of glasses in reducing the risk of SARS-CoV-2 infection. Face mask use was based on participants’ response to the end-of-follow-up survey. We found that the incidence of self-reported COVID-19 was 33% (aRR 1.33; 95% CI 1.03–1.72) higher in those wearing face masks often or sometimes, and 40% (aRR 1.40; 95% CI 1.08–1.82) higher in those wearing face masks almost always or always, compared to participants who reported wearing face masks never or almost never. We believe the observed increase in the incidence of infection associated with wearing a face mask is likely due to unobservable and hence nonadjustable differences between those wearing and not wearing a mask. Observational studies reporting on the relationship between face mask use and risk of respiratory infections should be interpreted cautiously, and more randomized trials are needed.