Establishing freedom from disease is a key component of surveillance and may have direct consequences for trade and economy. Transboundary populations pose challenges in terms of variable legislation, efforts, and data availability between countries, often limiting surveillance efficiency. Chronic wasting disease (CWD) is a contagious prion disease of cervids. The long incubation period and slow initial epidemic growth make it notoriously difficult to detect CWD in the early phase of an epidemic. The recent emergence of CWD in wild reindeer in Norway poses a threat to approximately 250,000 semi-domesticated reindeer in Norway and 250,000 in Sweden, including transboundary populations. Here, we provide a first analysis of surveillance data (2016-2022) from all reindeer districts in Norway and Sweden to determine the probability of freedom from CWD infection. During the six years, 6017 semi-domesticated reindeer were tested in Sweden and 51,974 in Norway. Most samples came from healthy slaughtered animals (low risk). Reindeer use large and remote areas and (high risk) samples from fallen stock and animals with clinical signs were difficult to obtain. A scenario tree model was run for seven different set of values for the input parameters (design prevalence within and between districts, probability of introduction, and relative risks) to determine the effect on surveillance sensitivity. At the national level, the mean probability of disease freedom was 59.0 % in Sweden and 87.0 % in Norway by 2021. The most marked effect on sensitivity was varying the design prevalence both within and between districts. Uncertainty about relative risk ratios affected sensitivity for Sweden more than for Norway, due to the higher proportion of animals in the high-risk group in the former (13.8 % vs. 2.1 %, respectively). A probability of disease freedom of 90 % or higher was reached in 8.2 % of the 49 districts in Sweden and 43.5 % of the 46 districts in Norway for a design prevalence of 0.5 %. The probability of freedom remained below 60 % in 29 districts (59.2 %) in Sweden and 10 districts (21.7 %) in Norway. At the national level, only Norway had a sufficiently large number of samples to reach a probability of more than 95 % of disease freedom within a period of 10 years. Our cross-border assessment forms an important knowledge base for designing future surveillance efforts depending on the spatial pattern of prevalence of CWD and risk of spread.

The aim of this study is to analyze the spatiotemporal risk of congenital syphilis (CS) in high-prevalence areas in the city of São Paulo, SP, Brazil, and to evaluate its relationship with socioeconomic, demographic, and environmental variables. An ecological study was conducted based on secondary CS data with spatiotemporal components collected from 310 areas between 2010 and 2016. The data were modeled in a Bayesian context using the integrated nested Laplace approximation (INLA) method. Risk maps showed an increasing CS trend over time and highlighted the areas that presented the highest and lowest risk in each year. The model showed that the factors positively associated with a higher risk of CS were the Gini index and the proportion of women aged 18-24 years without education or with incomplete primary education, while the factors negatively associated were the proportion of women of childbearing age and the mean per capita income.

Extreme temperatures and air pollution have raised widespread concerns about their impact on population health.
To explore the quantitative exposure risks of high/low temperatures and types of air pollutants on the health of various populations in urban areas in China, this study assessed the effects of temperature and air pollutants on daily non-accidental deaths in Rencheng District, Jining City, China from 2019 to 2021.
A combination of Poisson regression models and distributed lag non-linear models was used to examine the relationships between temperature, air pollutants, and daily non-accidental deaths. We found that temperature and air pollutants had a significant non-linear effect on non-accidental mortality. Both high and low temperatures had a noticeable impact on non-accidental deaths, with heat effects occurring immediately and lasting 2-3 days, while cold effects lasted for 6-12 days. The relative risks of non-accidental deaths from PM2.5, NO2, and SO2 were highest in winter and lowest in autumn. The relative risk of non-accidental deaths from O3 was highest in spring, with no significant variations in other seasons. Older adults (≥75) and outdoor workers were at the greatest risk from temperature and air pollutant exposure.
Exposure to extreme temperatures and air pollutants in the Rencheng District was associated with an increased mortality rate. Under the influence of climate change, it is necessary for policymakers to take measures to reduce the risk of non-accidental deaths among residents.

UNASSIGNED: Considering the opposite outcome-for example, survival instead of death-may affect conclusions about which subpopulation benefits more from a treatment or suffers more from an exposure.
UNASSIGNED: For case studies on death following COVID-19 and bankruptcy following melanoma, we compute and interpret the relative risk, odds ratio, and risk difference for different age groups. Since there is no established effect measure or outcome for either study, we redo these analyses for survival and solvency.
UNASSIGNED: In a case study on COVID-19 that ignores confounding, the relative risk of death suggested that 40-49-year-old Mexicans with COVID-19 suffered more from their unprepared healthcare system, using Italy\'s system as a baseline, than their 60-69-year-old counterparts. The relative risk of survival and the risk difference suggested the opposite conclusion. A similar phenomenon occurred in a case study on bankruptcy following melanoma treatment.
UNASSIGNED: To increase transparency around this paradox, researchers reporting one outcome should note if considering the opposite outcome would yield different conclusions. When possible, researchers should also report or estimate underlying risks alongside effect measures.

OBJECTIVE: A recent paper by Doi et al. advocated completely replacing the relative risk (RR) with the odds ratio (OR) as the effect measure in clinical trials and meta-analyses with binary outcomes. Besides some practical advantages of RR over OR, Doi et al.\'s key assumption that the OR is \"portable\" in the meta-analysis, that is, study-specific ORs are likely not correlated with baseline risks, was not well justified.
UNASSIGNED: We summarized Spearman\'s rank correlation coefficient between study-specific ORs and baseline risks in 40,243 meta-analyses from the Cochrane Database of Systematic Reviews.
RESULTS: Study-specific ORs tend to be higher in studies with lower baseline risks of disease for most meta-analyses in Cochrane Database of Systematic Reviews. Using an actual meta-analysis example, we demonstrate that there is a strong negative correlation between OR (RR or RD) with the baseline risk and the conditional effects notably vary with baseline risks.
CONCLUSIONS: Replacing RR or RD with OR is currently unadvisable in clinical trials and meta-analyses. It is possible that no effect measure is \"portable\" in a meta-analysis. In addition to the overall (or marginal) effect, we suggest presenting the conditional effect based on the baseline risk using a bivariate generalized linear mixed model.

With a recent surge of the new severe acute respiratory syndrome-coronavirus 2 (SARS-Cov-2, COVID-19) in South Korea, this study attempts to investigate the effects of environmental conditions such as air pollutants (PM2.5) and meteorological covariate (Temperature) on COVID-19 transmission in Seoul. To account for unobserved heterogeneity in the daily confirmed cases of COVID-19 across 25 contiguous districts within Seoul, we adopt a full Bayesian hierarchical approach for the generalized linear mixed models. A formal statistical analysis suggests that there exists a positive correlation between a 7-day lagged effect of PM2.5 concentration and the number of confirmed COVID-19 cases, which implies an elevated risk of the infectious disease. Conversely, temperature has shown a negative correlation with the number of COVID-19 cases, leading to reduction in relative risks. In addition, we clarify that the random fluctuation in the relative risks of COVID-19 mainly originates from temporal aspects, whereas no significant evidence of variability in relative risks is observed in terms of spatial alignment of the 25 districts. Nevertheless, this study provides empirical evidence using model-based formal assessments regarding COVID-19 infection risks in 25 districts of Seoul from a different perspective.

While much has been achieved, much remains to be accomplished in the science of preventing the spread of HIV infection. Clinical trials that are properly designed, conducted and analyzed are of integral importance in the pursuit of reliable insights about HIV prevention. As we build on previous scientific breakthroughs, there will be an increasing need for clinical trials to be designed to efficiently achieve insights without compromising their reliability and generalizability. Key design features should continue to include: 1) the use of randomization and evidence-based controls, 2) specifying the use of intention-to-treat analyses to preserve the integrity of randomization and to increase interpretability of results, 3) obtaining direct assessments of effects on clinical endpoints such as the risk of HIV infection, 4) using either superiority designs or non-inferiority designs with rigorous non-inferiority margins, and 5) enhancing generalizability through the choice of a relative risk rather than risk difference metric. When interventions have complementary and potentially synergistic effects, factorial designs should be considered to increase efficiency as well as to obtain clinically important insights about interaction and the contribution of component interventions to the efficacy and safety of combination regimens. Key trial conduct issues include timely enrollment of participants at high HIV risk recruited from populations with high viral burden, obtaining \'best real-world achievable\' levels of adherence to the interventions being assessed and ensuring high levels of retention. High quality of trial conduct occurs through active rather than passive monitoring, using pre-specified targeted levels of performance with defined methods to achieve those targets. During trial conduct, active monitoring of the performance standards not only holds the trial leaders accountable but also can assist in the development and implementation of creative alternative approaches to increase the quality of trial conduct. Designing, conducting and analyzing HIV prevention trials with the quality needed to obtain reliable insights is an ethical as well as scientific imperative.

Given the role of exposures related to residence in the development of nasopharyngeal carcinoma (NPC) has not been well explored, present study aims to investigate the magnitude and pattern of associations for NPC with lifelong residential exposures.
We carried out a multi-center, population-based case-control study with 2533 incident NPC cases and 2597 randomly selected population controls in southern China between 2010 and 2014. We performed multivariate logistic regression to estimate odds ratios (ORs) with 95% confidence intervals (CIs) for the risk of NPC associated with residential exposures.
Compared with those living in a building over lifetime, risk of NPC was higher for individuals living in a cottage (OR: 1.56; 95% CI: 1.34-1.81) or in a boat (3.87; 2.07-7.21). NPC risk was also increased in individuals using wood (1.34; 1.03-1.75), coal (1.70; 1.17-2.47), or kerosene (3.58; 1.75-7.36) vs. using gas/electricity as cooking fuel; using well water (1.57; 1.34-1.83), river water (1.80; 1.47-2.21), or spring/pond/stream water (2.03; 1.70-2.41) vs. tap water for source of drinking water; living in houses with smaller-sized vs. larger windows in the bedroom (3.08; 2.46-3.86), hall (1.89; 1.55-2.31) or kitchen (1.67; 1.34-2.08); and increasing exposure to cooking smoke [(1.53; 1.20-1.94) for high exposure)] or burned incense [(1.59; 1.31-1.95) for daily use)]. Weighted Cox regression analysis corroborated these results.
Poorer residential conditions and household air pollution are associated with an increased risk of NPC. Large-scale studies in other populations or longitudinal studies are warranted to further corroborate these findings.

OBJECTIVE: To examine the magnitude of sex differences in survival from the coronavirus disease 2019 (COVID-19) in Europe across age groups and regions. We hypothesized that men have a higher mortality than women at any given age but that sex differences will decrease with age as only the healthiest men survive to older ages.
METHODS: We used population data from the Institut National D\'Études Démographiques on cumulative deaths due to COVID-19 from February to June 2020 in 10 European regions: Denmark, Norway, Sweden, The Netherlands, England and Wales, France, Germany, Italy, Spain and Portugal. For each region, we calculated cumulative mortality rates stratified by age and sex and corresponding relative risks for men vs. women.
RESULTS: The relative risk of dying from COVID-19 was higher for men than for women in almost all age groups in all regions. The overall relative risk ranged from 1.11 (95% confidence interval, CI 1.01-1.23) in Portugal to 1.54 (95% CI 1.49-1.58) in France. In most regions, sex differences increased until the ages of 60-69 years, but decreased thereafter with the smallest sex difference at age 80+ years.
CONCLUSIONS: Despite variability in data collection and time coverage among regions, the study showed an overall similar pattern of sex differences in COVID-19 mortality in Europe.

We provide methods to estimate the confidence interval for the difference between two relative risks. Letting p0, p1, and p2 be the probabilities of an event in three groups (i.e. control, treatment 1, treatment 2), our methods estimate a confidence interval for r = p1/p0 - p2/p0. We highlight that our methods can handle small sample sizes, covariates, and study populations from multiple strata. We specifically developed these methods for vaccine trials to estimate the difference between two vaccine efficacies, where VE1 = 1 - p1/p0, VE2 = 1 - p2/p0 and r = VE2 - VE1. We showcase our methods by using interim data from one of these trials to suggest that one dose of the human papillomavirus vaccine may be as efficacious as two doses of the vaccine.