Addressing current limitations of household transmission studies by collecting contact data.

Modeling studies of household transmission data have helped characterize the role of children in influenza and COVID-19 epidemics. However, estimates from these studies may be biased since they do not account for the heterogeneous nature of household contacts. Here, we quantified the impact of contact heterogeneity between household members on the estimation of child relative susceptibility and infectivity. We simulated epidemics of SARS-CoV-2-like and influenza-like infections in a synthetic population of 1,000 households assuming heterogeneous contact levels. Relative contact frequencies were derived from a household contact study according to which contacts are more frequent in the father-mother pair, followed by the child-mother, child-child, and finally child-father pairs. Child susceptibility and infectivity were then estimated while accounting for heterogeneous contacts or not. When ignoring contact heterogeneity, child relative susceptibility was underestimated by approximately 20% in the two disease scenarios. Child relative infectivity was underestimated by 20% when children and adults had different infectivity levels. These results are sensitive to our assumptions of European-style household contact patterns; but they highlight that household studies collecting both disease and contact data are needed to assess the role of complex household contact behavior on disease transmission and improve estimation of key biological parameters.

Uncovering the endemic circulation of rabies in Cambodia.

In epidemiology, endemicity characterizes sustained pathogen circulation in a geographical area, which involves a circulation that is not being maintained by external introductions. Because it could potentially shape the design of public health interventions, there is an interest in fully uncovering the endemic pattern of a disease. Here, we use a phylogeographic approach to investigate the endemic signature of rabies virus (RABV) circulation in Cambodia. Cambodia is located in one of the most affected regions by rabies in the world, but RABV circulation between and within Southeast Asian countries remains understudied. Our analyses are based on a new comprehensive data set of 199 RABV genomes collected between 2014 and 2017 as well as previously published Southeast Asian RABV sequences. We show that most Cambodian sequences belong to a distinct clade that has been circulating almost exclusively in Cambodia. Our results thus point towards rabies circulation in Cambodia that does not rely on external introductions. We further characterize within-Cambodia RABV circulation by estimating lineage dispersal metrics that appear to be similar to other settings, and by performing landscape phylogeographic analyses to investigate environmental factors impacting the dispersal dynamic of viral lineages. The latter analyses do not lead to the identification of environmental variables that would be associated with the heterogeneity of viral lineage dispersal velocities, which calls for a better understanding of local dog ecology and further investigations of the potential drivers of RABV spread in the region. Overall, our study illustrates how phylogeographic investigations can be performed to assess and characterize viral endemicity in a context of relatively limited data.

Impact and mitigation of sampling bias to determine viral spread: Evaluating discrete phylogeography through CTMC modeling and structured coalescent model approximations.

Bayesian phylogeographic inference is a powerful tool in molecular epidemiological studies, which enables reconstruction of the origin and subsequent geographic spread of pathogens. Such inference is, however, potentially affected by geographic sampling bias. Here, we investigated the impact of sampling bias on the spatiotemporal reconstruction of viral epidemics using Bayesian discrete phylogeographic models and explored different operational strategies to mitigate this impact. We considered the continuous-time Markov chain (CTMC) model and two structured coalescent approximations (Bayesian structured coalescent approximation [BASTA] and marginal approximation of the structured coalescent [MASCOT]). For each approach, we compared the estimated and simulated spatiotemporal histories in biased and unbiased conditions based on the simulated epidemics of rabies virus (RABV) in dogs in Morocco. While the reconstructed spatiotemporal histories were impacted by sampling bias for the three approaches, BASTA and MASCOT reconstructions were also biased when employing unbiased samples. Increasing the number of analyzed genomes led to more robust estimates at low sampling bias for the CTMC model. Alternative sampling strategies that maximize the spatiotemporal coverage greatly improved the inference at intermediate sampling bias for the CTMC model, and to a lesser extent, for BASTA and MASCOT. In contrast, allowing for time-varying population sizes in MASCOT resulted in robust inference. We further applied these approaches to two empirical datasets: a RABV dataset from the Philippines and a SARS-CoV-2 dataset describing its early spread across the world. In conclusion, sampling biases are ubiquitous in phylogeographic analyses but may be accommodated by increasing the sample size, balancing spatial and temporal composition in the samples, and informing structured coalescent models with reliable case count data.

Correction: Mathematical modelling and phylodynamics for the study of dog rabies dynamics and control: A scoping review.

[This corrects the article DOI: 10.1371/journal.pntd.0009449.].

A cross-sectional study on infectious health risks regarding freshwater sports practice in Brittany, France.

Freshwater sports expose practitioners to pathogens in the water environment and may result in infection. In French Brittany, these infections are particularly worrying, especially since 2016 with an increase in the incidence of leptospirosis reaching 1 case per 100,000 inhabitants, which represents the highest incidence observed since 1920. We aimed to estimate the prevalence of infectious diseases related to freshwater sports practice and to identify the factors associated with these infections among freshwater sports licensees in Brittany, France. From March 18, 2019, to May 8, 2019, we interviewed freshwater sports licensees (online study) and club presidents and instructors (phone study) in Brittany. Licensee participants were 18 years old or more and practiced at least one freshwater sport in one of the 79 Brittany clubs. We used logistic regression models to study the association between our variables of interest and potential risk factors. In total, 551 licensees (20.3% of the total number of licensees) and 38 clubs (48.1%) were surveyed. Among the licensees, 29 (5.3%) reported being diagnosed with leptospirosis, of which 12 (41.3%) occurred in the last 5 years. The most reported symptoms were skin irritation/itchy skin (24.3%) and 39 individuals (7.1%) reported at least one hospitalization in their lifetime for a disease related to freshwater sports. The occurrence of leptospirosis was negatively associated with boarding from a pontoon (odds ratio (OR)=0.20, 95% confidence interval (95% CI) 0.06-0.56), practicing for less than 4 years (OR=0.17, 95% CI 0.04-0.56) compared to more than 10 years, and the occurrence of leptospirosis was positively associated with taking a soapy shower after practice (OR=4.38, 95% CI 1.90-10.51). Eskimo roll was positively associated with the occurrence of otitis and conjunctivitis (OR=3.22, 95% CI 1.82-6.03), and skin irritation/itchy skin (OR=1.66, 95% CI 0.99-2.84). Otitis, conjunctivitis, and skin irritation/itchy skin are the most commonly reported freshwater sport-related diseases in French Brittany. Despite a good level of knowledge of prevention measures, their implementation by licensees and clubs remains low. Further studies are needed to identify practices associated with infectious risk in freshwater sports.

An ensemble model based on early predictors to forecast COVID-19 health care demand in France.

Short-term forecasting of the COVID-19 pandemic is required to facilitate the planning of COVID-19 health care demand in hospitals. Here, we evaluate the performance of 12 individual models and 19 predictors to anticipate French COVID-19-related health care needs from September 7, 2020, to March 6, 2021. We then build an ensemble model by combining the individual forecasts and retrospectively test this model from March 7, 2021, to July 6, 2021. We find that the inclusion of early predictors (epidemiological, mobility, and meteorological predictors) can halve the rms error for 14-d­ahead forecasts, with epidemiological and mobility predictors contributing the most to the improvement. On average, the ensemble model is the best or second-best model, depending on the evaluation metric. Our approach facilitates the comparison and benchmarking of competing models through their integration in a coherent analytical framework, ensuring that avenues for future improvements can be identified.

Impact of BNT162b2 Vaccination and Isolation on SARS-CoV-2 Transmission in Israeli Households: An Observational Study.

Several studies have characterized the effectiveness of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. However, estimates of their impact on transmissibility remain limited. Here, we evaluated the impact of isolation and vaccination (7 days after the second dose) on SARS-CoV-2 transmission within Israeli households. From December 2020 to April 2021, confirmed cases were identified among health-care workers of the Sheba Medical Centre and their family members. Recruited households were followed up with repeated PCR for at least 10 days after case confirmation. Data were analyzed using a data augmentation Bayesian framework. A total of 210 households with 215 index cases were enrolled; 269 out of 667 (40%) susceptible household contacts developed a SARS-CoV-2 infection. Of those, 170 (63%) developed symptoms. Compared with unvaccinated and unisolated adult/teenager (aged >12 years) contacts, vaccination reduced the risk of infection among unisolated adult/teenager contacts (relative risk (RR) = 0.21, 95% credible interval (CrI): 0.08, 0.44), and isolation reduced the risk of infection among unvaccinated adult/teenager (RR = 0.12, 95% CrI: 0.06, 0.21) and child contacts (RR = 0.17, 95% CrI: 0.08, 0.32). Infectivity was reduced in vaccinated cases (RR = 0.25, 95% CrI: 0.06, 0.77). Within households, vaccination reduces both the risk of infection and of transmission if infected. When contacts were unvaccinated, isolation also led to important reductions in the risk of transmission.

On the Use of Phylogeographic Inference to Infer the Dispersal History of Rabies Virus: A Review Study.

Rabies is a neglected zoonotic disease which is caused by negative strand RNA-viruses belonging to the genus Lyssavirus. Within this genus, rabies viruses circulate in a diverse set of mammalian reservoir hosts, is present worldwide, and is almost always fatal in non-vaccinated humans. Approximately 59,000 people are still estimated to die from rabies each year, leading to a global initiative to work towards the goal of zero human deaths from dog-mediated rabies by 2030, requiring scientific efforts from different research fields. The past decade has seen a much increased use of phylogeographic and phylodynamic analyses to study the evolution and spread of rabies virus. We here review published studies in these research areas, making a distinction between the geographic resolution associated with the available sequence data. We pay special attention to environmental factors that these studies found to be relevant to the spread of rabies virus. Importantly, we highlight a knowledge gap in terms of applying these methods when all required data were available but not fully exploited. We conclude with an overview of recent methodological developments that have yet to be applied in phylogeographic and phylodynamic analyses of rabies virus.

Mathematical modelling and phylodynamics for the study of dog rabies dynamics and control: A scoping review.

BACKGROUND: Rabies is a fatal yet vaccine-preventable disease. In the last two decades, domestic dog populations have been shown to constitute the predominant reservoir of rabies in developing countries, causing 99% of human rabies cases. Despite substantial control efforts, dog rabies is still widely endemic and is spreading across previously rabies-free areas. Developing a detailed understanding of dog rabies dynamics and the impact of vaccination is essential to optimize existing control strategies and developing new ones. In this scoping review, we aimed at disentangling the respective contributions of mathematical models and phylodynamic approaches to advancing the understanding of rabies dynamics and control in domestic dog populations. We also addressed the methodological limitations of both approaches and the remaining issues related to studying rabies spread and how this could be applied to rabies control. METHODOLOGY/PRINCIPAL FINDINGS: We reviewed how mathematical modelling of disease dynamics and phylodynamics have been developed and used to characterize dog rabies dynamics and control. Through a detailed search of the PubMed, Web of Science, and Scopus databases, we identified a total of n = 59 relevant studies using mathematical models (n = 30), phylodynamic inference (n = 22) and interdisciplinary approaches (n = 7). We found that despite often relying on scarce rabies epidemiological data, mathematical models investigated multiple aspects of rabies dynamics and control. These models confirmed the overwhelming efficacy of massive dog vaccination campaigns in all settings and unraveled the role of dog population structure and frequent introductions in dog rabies maintenance. Phylodynamic approaches successfully disentangled the evolutionary and environmental determinants of rabies dispersal and consistently reported support for the role of reintroduction events and human-mediated transportation over long distances in the maintenance of rabies in endemic areas. Potential biases in data collection still need to be properly accounted for in most of these analyses. Finally, interdisciplinary studies were determined to provide the most comprehensive assessments through hypothesis generation and testing. They also represent new avenues, especially concerning the reconstruction of local transmission chains or clusters through data integration. CONCLUSIONS/SIGNIFICANCE: Despite advances in rabies knowledge, substantial uncertainty remains regarding the mechanisms of local spread, the role of wildlife in dog rabies maintenance, and the impact of community behavior on the efficacy of control strategies including vaccination of dogs. Future integrative approaches that use phylodynamic analyses and mechanistic models within a single framework could take full advantage of not only viral sequences but also additional epidemiological information as well as dog ecology data to refine our understanding of rabies spread and control. This would represent a significant improvement on past studies and a promising opportunity for canine rabies research in the frame of the One Health concept that aims to achieve better public health outcomes through cross-sector collaboration.

The effect of human mobility and control measures on the COVID-19 epidemic in China.

The ongoing COVID-19 outbreak has expanded rapidly throughout China. Major behavioral, clinical, and state interventions are underway currently to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, have affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was well explained by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases are still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China have substantially mitigated the spread of COVID-19.

The effect of human mobility and control measures on the COVID-19 epidemic in China.

The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.