Effectiveness of rVSV-ZEBOV vaccination during the 2018-20 Ebola virus disease epidemic in the Democratic Republic of the Congo: a retrospective test-negative study.

Background: The recombinant vesicular stomatitis virus-Zaire Ebola virus (rVSV-ZEBOV) vaccine is the only WHO prequalified vaccine recommended for use to respond to outbreaks of Ebola virus (species Zaire ebolavirus) by WHO's Strategic Advisory Group of Experts on Immunization. Despite the vaccine's widespread use during several outbreaks, no real-world effectiveness estimates are currently available in the literature.

Methods: We conducted a retrospective test-negative analysis to estimate effectiveness of rVSV-ZEBOV vaccination against Ebola virus disease during the 2018-20 epidemic in the Democratic Republic of the Congo, using data on suspected Ebola virus disease cases collected from Ebola treatment centres.

Quantifying the impact of hospital catchment area definitions on hospital admissions forecasts: COVID-19 in England, September 2020-April 2021.

Background: Defining healthcare facility catchment areas is a key step in predicting future healthcare demand in epidemic settings. Forecasts of hospitalisations can be informed by leading indicators measured at the community level. However, this relies on the definition of so-called catchment areas or the geographies whose populations make up the patients admitted to a given hospital, which are often not well-defined.

Evaluating the use of social contact data to produce age-specific short-term forecasts of SARS-CoV-2 incidence in England.

Mathematical and statistical models can be used to make predictions of how epidemics may progress in the near future and form a central part of outbreak mitigation and control. Renewal equation based models allow inference of epidemiological parameters from historical data and forecast future epidemic dynamics without requiring complex mechanistic assumptions. However, these models typically ignore interaction between age groups, partly due to challenges in parameterising a time varying interaction matrix.

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations.

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022.

The association of COVID-19 incidence with temperature, humidity, and UV radiation - A global multi-city analysis.

Background And Aim: The associations between COVID-19 transmission and meteorological factors are scientifically debated. Several studies have been conducted worldwide, with inconsistent findings. However, often these studies had methodological issues, e.

Effect of Fatigue on Health-Related Quality of Life and Work Productivity in Psoriatic Arthritis: Findings From a Real-World Survey.

Objective: To evaluate fatigue frequency and severity among patients with psoriatic arthritis (PsA) and assess the effect of fatigue severity on patient-reported outcome measures (PROMs) assessing quality of life, function, and work productivity.

Methods: Data were derived from the Adelphi Disease Specific Programme, a cross-sectional survey conducted in 2018 in the United States and Europe. Patients had physician-confirmed PsA.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.

Patient-psychiatrist discordance and drivers of prescribing long-acting injectable antipsychotics for schizophrenia management in the real-world: a point-in-time survey.

Background: To assess discordance between psychiatrists and their patients with schizophrenia regarding disease management and understand drivers of prescribing long-acting injectable (LAI) antipsychotics.

Methods: Data were collected via the Adelphi Schizophrenia Disease Specific Programme™, a point-in-time real-world international survey of psychiatrists and their consulting patients with schizophrenia, conducted in 2019. Psychiatrists completed an attitudinal survey on schizophrenia management and provided patient profiles for their next 10 adult consulting patients.

Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level.

Background: Forecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources.

Physician-reported Clinical Unmet Needs, Burden and Treatment Patterns of Paediatric Psoriasis Patients: A US and EU Real-world Evidence Study.

This study is a retrospective analysis using data collected from the Adelphi Paediatric Psoriasis Disease-Specific Programme cross-sectional survey. Despite being treated for their psoriasis, a substantial proportion of paediatric patients presented with moderate (18.3%) or severe (1.

Correction: Practical considerations for measuring the effective reproductive number, Rt.

[This corrects the article DOI: 10.1371/journal.pcbi.

Associations Between Relapses and Psychosocial Outcomes in Patients With Schizophrenia in Real-World Settings in the United States.

To assess associations between relapses and psychosocial outcomes in adult patients with schizophrenia treated in United States (US) healthcare settings. Data were derived from a point-in-time survey of psychiatrists and their patients with schizophrenia conducted across the US, France, Spain, China, and Japan between July and October 2019. For the purposes of this analysis, only data from US practitioners and patients were included.

Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level.

Background: Forecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources.

A cross-sectional analysis of meteorological factors and SARS-CoV-2 transmission in 409 cities across 26 countries.

There is conflicting evidence on the influence of weather on COVID-19 transmission. Our aim is to estimate weather-dependent signatures in the early phase of the pandemic, while controlling for socio-economic factors and non-pharmaceutical interventions. We identify a modest non-linear association between mean temperature and the effective reproduction number (R) in 409 cities in 26 countries, with a decrease of 0.

How to improve outbreak response: a case study of integrated outbreak analytics from Ebola in Eastern Democratic Republic of the Congo.

The emerging field of outbreak analytics calls attention to the need for data from multiple sources to inform evidence-based decision making in managing infectious diseases outbreaks. To date, these approaches have not systematically integrated evidence from social and behavioural sciences. During the 2018-2020 Ebola outbreak in Eastern Democratic Republic of the Congo, an innovative solution to systematic and timely generation of integrated and actionable social science evidence emerged in the form of the Cellulle d'Analyse en Sciences Sociales (Social Sciences Analytics Cell) (CASS), a social science analytical cell.

Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection.

As several countries gradually release social distancing measures, rapid detection of new localized COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ASMODEE (automatic selection of models and outlier detection for epidemics), a new tool for detecting sudden changes in COVID-19 incidence. Our approach relies on automatically selecting the best (fitting or predicting) model from a range of user-defined time series models, excluding the most recent data points, to characterize the main trend in an incidence.

Exploring surveillance data biases when estimating the reproduction number: with insights into subpopulation transmission of COVID-19 in England.

The time-varying reproduction number (: the average number of secondary infections caused by each infected person) may be used to assess changes in transmission potential during an epidemic. While new infections are not usually observed directly, they can be estimated from data. However, data may be delayed and potentially biased.

Implications of the school-household network structure on SARS-CoV-2 transmission under school reopening strategies in England.

In early 2020 many countries closed schools to mitigate the spread of SARS-CoV-2. Since then, governments have sought to relax the closures, engendering a need to understand associated risks. Using address records, we construct a network of schools in England connected through pupils who share households.

Practical considerations for measuring the effective reproductive number, Rt.

Estimation of the effective reproductive number Rt is important for detecting changes in disease transmission over time. During the Coronavirus Disease 2019 (COVID-19) pandemic, policy makers and public health officials are using Rt to assess the effectiveness of interventions and to inform policy. However, estimation of Rt from available data presents several challenges, with critical implications for the interpretation of the course of the pandemic.

Practical considerations for measuring the effective reproductive number, .

Estimation of the effective reproductive number, , is important for detecting changes in disease transmission over time. During the COVID-19 pandemic, policymakers and public health officials are using to assess the effectiveness of interventions and to inform policy. However, estimation of from available data presents several challenges, with critical implications for the interpretation of the course of the pandemic.

Correlations between stochastic endemic infection in multiple interacting subpopulations.

Heterogeneity plays an important role in the emergence, persistence and control of infectious diseases. Metapopulation models are often used to describe spatial heterogeneity, and the transition from random- to heterogeneous-mixing is made by incorporating the interaction, or coupling, within and between subpopulations. However, such couplings are difficult to measure explicitly; instead, their action through the correlations between subpopulations is often all that can be observed.

Correlations between stochastic epidemics in two interacting populations.

It is increasingly apparent that heterogeneity in the interaction between individuals plays an important role in the dynamics, persistence, evolution and control of infectious diseases. In epidemic modelling two main forms of heterogeneity are commonly considered: spatial heterogeneity due to the segregation of populations and heterogeneity in risk at the same location. The transition from random-mixing to heterogeneous-mixing models is made by incorporating the interaction, or coupling, within and between subpopulations.