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What to Make of Covid-19 Hot SpotsIn this audio interview conducted on May 17, 2022, the editors discuss varying rates of infection and illness around the world and what this heterogeneity means for physicians.

We assessed the spatiotemporal dynamics of Oropouche fever in Brazil during 2015-2024. We found the number of cases substantially increased during that period, particularly in the Amazon region. Our findings underscore the need for improved surveillance and public health measures in response to the disease's potential spread beyond endemic areas.

Anxiety/stress-related disorders have been associated with multiple diseases, whereas a comprehensive assessment of the structure and interplay of subsequent associated diseases and their genetic underpinnings is lacking. Here, we first identify 136, out of 454 tested, medical conditions associated with incident anxiety/stress-related disorders attended in specialized care using a population-based cohort from the nationwide Swedish Patient Register, comprising 70,026 patients with anxiety/stress-related disorders and 1:10 birth year- and sex-matched unaffected individuals. By combining findings from the comorbidity network and disease trajectory analyses, we identify five robust disease clusters to be associated with a prior diagnosis of anxiety/stress-related disorders, featured by predominance of psychiatric disorders, eye diseases, ear diseases, cardiovascular diseases, and skin and genitourinary diseases. These five clusters and their featured diseases are largely validated in the UK Biobank. GWAS analyses based on the UK Biobank identify 3, 33, 40, 4, and 16 significantly independent single nucleotide polymorphisms for the link to the five disease clusters, respectively, which are mapped to several distinct risk genes and biological pathways. These findings motivate further mechanistic explorations and aid early risk assessment for cluster-based disease prevention among patients with newly diagnosed anxiety/stress-related disorders in specialized care. In this study, the authors found five disease clusters associated with a prior diagnosis of anxiety/stress-related disorders, and identified several underlying genetic components. These findings may aid mechanistic exploration and risk management for health decline among those patients.

Risks for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care personnel (HCP) are unclear. To evaluate the risk factors associated with SARS-CoV-2 seropositivity among HCP with the a priori hypothesis that community exposure but not health care exposure was associated with seropositivity. This cross-sectional study was conducted among volunteer HCP at 4 large health care systems in 3 US states. Sites shared deidentified data sets, including previously collected serology results, questionnaire results on community and workplace exposures at the time of serology, and 3-digit residential zip code prefix of HCP. Site-specific responses were mapped to a common metadata set. Residential weekly coronavirus disease 2019 (COVID-19) cumulative incidence was calculated from state-based COVID-19 case and census data. Model variables included demographic (age, race, sex, ethnicity), community (known COVID-19 contact, COVID-19 cumulative incidence by 3-digit zip code prefix), and health care (workplace, job role, COVID-19 patient contact) factors. The main outcome was SARS-CoV-2 seropositivity. Risk factors for seropositivity were estimated using a mixed-effects logistic regression model with a random intercept to account for clustering by site. Among 24 749 HCP, most were younger than 50 years (17 233 [69.6%]), were women (19 361 [78.2%]), were White individuals (15 157 [61.2%]), and reported workplace contact with patients with COVID-19 (12 413 [50.2%]). Many HCP worked in the inpatient setting (8893 [35.9%]) and were nurses (7830 [31.6%]). Cumulative incidence of COVID-19 per 10 000 in the community up to 1 week prior to serology testing ranged from 8.2 to 275.6; 20 072 HCP (81.1%) reported no COVID-19 contact in the community. Seropositivity was 4.4% (95% CI, 4.1%-4.6%; 1080 HCP) overall. In multivariable analysis, community COVID-19 contact and community COVID-19 cumulative incidence were associated with seropositivity (community contact: adjusted odds ratio [aOR], 3.5; 95% CI, 2.9-4.1; community cumulative incidence: aOR, 1.8; 95% CI, 1.3-2.6). No assessed workplace factors were associated with seropositivity, including nurse job role (aOR, 1.1; 95% CI, 0.9-1.3), working in the emergency department (aOR, 1.0; 95% CI, 0.8-1.3), or workplace contact with patients with COVID-19 (aOR, 1.1; 95% CI, 0.9-1.3). In this cross-sectional study of US HCP in 3 states, community exposures were associated with seropositivity to SARS-CoV-2, but workplace factors, including workplace role, environment, or contact with patients with known COVID-19, were not. These findings provide reassurance that current infection prevention practices in diverse health care settings are effective in preventing transmission of SARS-CoV-2 from patients to HCP.

Nontuberculous mycobacteria (NTM) infections are caused by environmental exposure. We describe spatial distribution of NTM infections and associations with sociodemographic factors and flooding in Missouri, USA. Our retrospective analysis of mycobacterial cultures reported to the Missouri Department of Health and Social Services surveillance system during January 1, 2008-December 31, 2019, detected geographic clusters of infection. Multilevel Poisson regression quantified small-area geographic variations and identified characteristics associated with risk for infection. Median county-level NTM infection rate was 66.33 (interquartile range 51-91)/100,000 persons. Risk of clustering was significantly higher in rural areas (rate ratio 2.82, 95% CI 1.90-4.19) and in counties with >5 floodings per year versus no flooding (rate ratio 1.38, 95% CI 1.26-1.52). Higher risk for NTM infection was associated with older age, rurality, and more flooding. Clinicians and public health professionals should be aware of increased risk for NTM infections, especially in similar environments.

COVID-19 epidemics have varied dramatically in nature across the United States, where some counties have clear peaks in infections, and others have had a multitude of unpredictable and non-distinct peaks. Our lack of understanding of how the pandemic has evolved leads to increasing errors in our ability to predict the spread of the disease. This work seeks to explain this diversity in epidemic progressions by considering an extension to the compartmental SEIRD model. The model we propose uses a neural network to predict the infection rate as a function of both time and the disease’s prevalence. We provide a methodology for fitting this model to available county-level data describing aggregate cases and deaths. Our method uses Expectation-Maximization to overcome the challenge of partial observability, due to the fact that the system’s state is only partially reflected in available data. We fit a single model to data from multiple counties in the United States exhibiting different behavior. By simulating the model, we show that it can exhibit both single peak and multi-peak behavior, reproducing behavior observed in counties both in and out of the training set. We then compare the error of simulations from our model with a standard SEIRD model, and show that ours substantially reduces errors. We also use simulated data to compare our methodology for handling partial observability with a standard approach, showing that ours is significantly better at estimating the values of unobserved quantities.

We aim to identify those measures that effectively control the spread of SARS-CoV-2 in Austrian schools. Using cluster tracing data we calibrate an agent-based epidemiological model and consider situations where the B1.617.2 (delta) virus strain is dominant and parts of the population are vaccinated to quantify the impact of non-pharmaceutical interventions (NPIs) such as room ventilation, reduction of class size, wearing of masks during lessons, vaccinations, and school entry testing by SARS-CoV2-antigen tests. In the data we find that 40% of all clusters involved no more than two cases, and 3% of the clusters only had more than 20 cases. The model shows that combinations of NPIs together with vaccinations are necessary to allow for a controlled opening of schools under sustained community transmission of the SARS-CoV-2 delta variant. For plausible vaccination rates, primary (secondary) schools require a combination of at least two (three) of the above NPIs. How to safely maintain open schools during a pandemic is still controversial. Here, the authors aim to identify those measures that effectively control the spread of SARS-CoV-2 in Austrian schools, with an agent-based mathematical model.

Digital contact tracing apps have been introduced globally as an instrument to contain the COVID-19 pandemic. Yet, privacy by design impedes both the evaluation of these tools and the deployment of evidence-based interventions to stimulate uptake. We combine an online panel survey with mobile tracking data to measure the actual usage of Germany’s official contact tracing app and reveal higher uptake rates among respondents with an increased risk of severe illness, but lower rates among those with a heightened risk of exposure to COVID-19. Using a randomized intervention, we show that informative and motivational video messages have very limited effect on uptake. However, findings from a second intervention suggest that even small monetary incentives can strongly increase uptake and help make digital contact tracing a more effective tool. Combining mobile tracking data and a survey experiment, Munzert et al. show that Germany’s contact tracing app is underused by those who socially distance less; however, even small cash incentives increased app uptake in the cohort.

Schistosomiasis is the second most important human parasitic disease in terms of socioeconomic impact, causing great morbidity and mortality, predominantly across the African continent. For intestinal schistosomiasis, severe morbidity manifests as periportal fibrosis (PPF) in which large tracts of macro-fibrosis of the liver, visible by ultrasound, can occlude the main portal vein leading to portal hypertension (PHT), sequelae such as ascites and collateral vasculature, and ultimately fatalities. For urogenital schistosomiasis, severe morbidity manifests as pathology throughout the urinary system and genitals, and is a definitive cause of squamous cell bladder carcinoma. Preventative chemotherapy (PC) programmes, delivered through mass drug administration (MDA) of praziquantel (PZQ), have been at the forefront of schistosomiasis control programmes in sub-Saharan Africa since their commencement in Uganda in 2003. However, despite many successes, ‘biological hotspots’ (as distinct from ‘operational hotspots’) of both persistent high transmission and morbidity remain. In some areas, this failure to gain control of schistosomiasis has devastating consequences, with not only persistently high infection intensities, but both “subtle” and severe morbidity remaining prevalent. These hotspots highlight the requirement to revisit research into severe morbidity and its mechanisms, a topic that has been out of favor during times of PC implementation. Indeed, the focality and spatially-structured epidemiology of schistosomiasis, its transmission persistence and the morbidity induced, has long suggested that gene-environmental-interactions playing out at the host-parasite interface are crucial. Here we review evidence of potential unique parasite factors, host factors, and their gene-environmental interactions in terms of explaining differential morbidity profiles in the human host. We then take the situation of schistosomiasis mansoni within the Albertine region of Uganda as a case study in terms of elucidating the factors behind the severe morbidity observed and the avenues and directions for future research currently underway within a new research and clinical trial programme (FibroScHot).

Melioidosis outbreaks in Taiwan frequently coincided with severe typhoons. Over a 20-year period, 782 cases of melioidosis were reported, with outbreaks often clustering in a specific hotspot area. We hypothesized that the unique hilly terrain in this hotspot trapped contaminated aerosols generated from northern to northwestern farming land within the area and restricted their spread beyond it. Across Taiwan, and particularly within the hotspot, weekly melioidosis incidence was significantly correlated with heavy rainfall and strong wind speed with time lags of 0, 1 and 2 weeks. When rainfall exceeded 200 mm and wind gust speeds reached over 20 m/sec, melioidosis outbreaks were frequently observed. Additionally, melioidosis incidence was associated with riverbank repair activities, indicating severe flooding caused by typhoons. Environmental confounding factors, such as CH₄, CO, NO, NO₂, NO x , O₃, particulate matter (PM) 10 , PM 2.5 , SO₂, and total hydrocarbon (THC), fluctuated seasonally but were not correlated with melioidosis cases. Aerosol sampling revealed that concentrations of contaminated aerosols were markedly higher north of the hill, where farming land was more prevalent, compared to the south, which had no farming land and was primarily residential. In addition to heavy rainfall and strong wind speed, shifts in wind direction from southwesterly to northwesterly during typhoons appeared to concentrate aerosols in the northern area but not in the south. Higher seropositive rates for Burkholderia pseudomallei antibodies in northern residents, compared to those in the south, further suggested increased exposure to pathogen-laden aerosols in the northern hotspot. This study demonstrated that heavy rainfall, combined with strong directional winds, generated high concentrations of contaminated aerosols from farming land in specific hilly terrains, leading to localized melioidosis outbreaks. It provided a valuable example of geographical, and climatic factors driving the formation of melioidosis hotspots in subtropical regions such as southern Taiwan.