Biology subjects

Edmunds, J.

Publications and source records attributed to Edmunds, J..

7 recordsLinked to original sources

bioRxiv2024

Drivers of Ixodes ricinus population dynamics in Northeast France: a Bayesian modelling approach

Ixodes ricinus is the primary vector for Lyme disease and tick-borne encephalitis across Europe. Despite playing a critical role in disease transmission dynamics, the environmental drivers of its complex life cycle have not been quantified using real-world data. To address this gap, we fitted a unique mechanistic model to a detailed 10-years longitudinal dataset from four sites in Northern France, where I. ricinus is abundant and Lyme disease and tick-borne encephalitis have been reported for decades, within a Bayesian framework. By incorporating key demographic processes and the influence of environmental conditions on these processes, our model estimated oviposition, hatching, and moulting rates across a range of temperature or saturation deficit, as well as questing and vertebrate host contact rates. Notably, moulting peaked at 14.2{degrees}C (95%HDI: 12.5-16.1{degrees}C), substantially lower than commonly suggested by laboratory-based studies, whereas oviposition and hatching peaked at 24.4{degrees}C (95%HDI: 10.9- 27.2{degrees}C) and 24.7{degrees}C (95%HDI: 17.8-27.2{degrees}C), respectively. Furthermore, vertebrate host contact rates significantly varied between the four study sites, with one site presenting up to 2.90 (95%HDI: 2.15-3.86) times higher contact rates than the other three sites. Additionally, we showed the importance of diapause in reproducing the observed seasonal population dynamics. For ticks overwintering through diapause, moulting in spring more accurately matched the predominantly unimodal questing activity patterns observed, compared to moulting in summer. Finally, model projections under several climate change scenarios indicated decreasing tick abundance trends over the next two decades. This study provides a foundation for models of I. ricinus-borne pathogen transmission and can be adapted to other Ixodidae populations of public health significance.

ecology↗

bioRxiv2021

Measuring the unknown: an estimator and simulation study for assessing case reporting during epidemics

The fraction of cases reported, known as reporting, is a key performance indicator in an outbreak response, and an essential factor to consider when modelling epidemics and assessing their impact on populations. Unfortunately, its estimation is inherently difficult, as it relates to the part of an epidemic which is, by definition, not observed. We introduce a simple statistical method for estimating reporting, initially developed for the response to Ebola in Eastern Democratic Republic of the Congo (DRC), 2018-2020. This approach uses transmission chain data typically gathered through case investigation and contact tracing, and uses the proportion of investigated cases with a known, reported infector as a proxy for reporting. Using simulated epidemics, we study how this method performs for different outbreak sizes and reporting levels. Results suggest that our method has low bias, reasonable precision, and despite sub-optimal coverage, usually provides estimates within close range (5-10%) of the true value. Being fast and simple, this method could be useful for estimating reporting in real-time in settings where person-to-person transmission is the main driver of the epidemic, and where case investigation is routinely performed as part of surveillance and contact tracing activities. Author summaryWhen responding to epidemics of infectious diseases, it is essential to estimate how many cases are not being reported. Unfortunately reporting, the proportion of cases actually observed, is difficult to estimate during an outbreak, as it typically requires large surveys to be conducted on the affected populations. Here, we introduce a method for estimating reporting from case investigation data, using the proportion of cases with a known, reported infector. We used simulations to test the performance of our approach by mimicking features of a recent Ebola epidemic in the Democratic Republic of the Congo. We found that despite some uncertainty in smaller outbreaks, our approach can be used to obtain informative ballpark estimates of reporting under most settings. This method is simple and computationally inexpensive, and can be used to inform the response to any epidemic in which transmission events can be uncovered by case investigation.

bioinformatics↗

bioRxiv2019

Zika virus seroprevalence declines and neutralization antibodies wane in adults following outbreaks in French Polynesia and Fiji

BackgroundSerosurveys published following major outbreaks of Zika virus (ZIKV) have so far shown a high level of seroprevalence from samples collected within 12 months of the first confirmed case. A common assumption is that ZIKV infection confers long-term protection against reinfection, preventing ZIKV from re-emerging in previously affected areas for many years. However, the long-term immune response to ZIKV following an outbreak remains poorly documented.\n\nMethodsWe compared results from eight serological surveys, with sample sizes ranging from 49 to 700, before and after known ZIKV outbreaks in the Pacific region: five from cross-sectional studies of schoolchildren and the general population in French Polynesia over a seven-year period; and three from a longitudinal cohort in Fiji over a four-year period.\n\nFindingsWe found strong evidence of a decline in seroprevalence in both countries over a two-year period following first reported ZIKV transmission. In the cohort in Fiji, there was also a significant decline in antibody titres against ZIKV. However, the decline in seroprevalence was concentrated in adults, while high seroprevalence persisted in children.\n\nInterpretationThe observed patterns of long-term anti-ZIKV antibody levels following outbreaks in the Pacific could be an early indication of the dynamics of population immunity in Latin America. Given that ZIKV antibody levels can wane substantially over time, follow-up seroprevalence studies and prospective clinical trial designs in Latin America may need to be revised, and assumptions about the potential for ZIKV to re-emerge may need to be revisited.\n\nFundingPacific Funds, ANR, MRC, Wellcome, Royal Society.

epidemiology↗

bioRxiv2018

Projecting the end of the Zika virus epidemic in Latin America: a modelling analysis

Background Zika virus (ZIKV) emerged in Latin America & the Caribbean (LAC) region in 2013, and has had serious implications for population health in the region. In 2016, the World Health Organization declared the ZIKV outbreak a Public Health Emergency of International Concern following a cluster of associated neurological disorders and neonatal malformations. In 2017, Zika cases declined, but future incidence in LAC remains uncertain due to gaps in our understanding, considerable variation in surveillance and a lack of a comprehensive collation of data from affected countries.\n\nMethods Our analysis combines information on confirmed and suspected Zika cases across LAC countries and a spatio-temporal dynamic transmission model for ZIKV infection to determine key transmission parameters and projected incidence in 91 major cities within 35 countries. Seasonality was determined by spatio-temporal estimates of Aedes aegypti vector capacity. We used country and state-level data from 2015 to mid-2017 to infer key model parameters, country-specific disease reporting rates, and the 2018 projected incidence. A 10-fold cross-validation approach was used to validate parameter estimates to out-of-sample epidemic trajectories.\n\nResults There was limited transmission in 2015, but in 2016 and 2017 there was sufficient opportunity for wide-spread ZIKV transmission in most cities, resulting in the depletion of susceptible individuals. We predict that the highest number of cases in 2018 within some Brazilian States (Sao Paulo and Rio de Janeiro), Colombia and French Guiana, but the estimated number of cases were no more than a few hundred. Model estimates of the timing of the peak in incidence were correlated (p<0.05) with the reported peak in incidence. The reporting rate varied across countries, with lower reporting rates for those with only confirmed cases compared to those who reported both confirmed and suspected cases.\n\nConclusions The findings suggest that the ZIKV epidemic is by and large over, with incidence projected to be low in most cities in LAC in 2018. Local low levels of transmission are probable but the estimated rate of infection suggests that most cities have a population with high levels of herd immunity.

epidemiology↗

bioRxiv2018

Unsupervised Extraction of Epidemic Syndromes from Participatory Influenza Surveillance Self-reported Symptoms

Seasonal influenza surveillance is usually carried out by sentinel general practitioners who compile weekly reports based on the number of influenza-like illness (ILI) clinical cases observed among visited patients. This practice for surveillance is generally affected by two main issues: i) reports are usually released with a lag of about one week or more, ii) the definition of a case of influenza-like illness based on patients symptoms varies from one surveillance system to the other, i.e. from one country to the other. The availability of novel data streams for disease surveillance can alleviate these issues; in this paper, we employed data from Influenzanet, a participatory web-based surveillance project which collects symptoms directly from the general population in real time. We developed an unsupervised probabilistic framework that combines time series analysis of symptoms counts and performs an algorithmic detection of groups of symptoms, hereafter called syndromes. Symptoms counts were collected through the participatory web-based surveillance platforms of a consortium called Influenzanet which is found to correlate with Influenza-like illness incidence as detected by sentinel doctors. Our aim is to suggest how web-based surveillance data can provide an epidemiological signal capable of detecting influenza-like illness temporal trends without relying on a specific case definition. We evaluated the performance of our framework by showing that the temporal trends of the detected syndromes closely follow the ILI incidence as reported by the traditional surveillance, and consist of combinations of symptoms that are compatible with the ILI definition. The proposed framework was able to predict quite accurately the ILI trend of the forthcoming influenza season based only on the available information of the previous years. Moreover, we assessed the generalisability of the approach by evaluating its potentials for the detection of gastrointestinal syndromes. We evaluated the approach against the traditional surveillance data and despite the limited amount of data, the gastrointestinal trend was successfully detected. The result is a real-time flexible surveillance and prediction tool that is not constrained by any disease case definition.\n\nAuthor summaryThis study suggests how web-based surveillance data can provide an epidemiological signal capable of detecting influenza-like illness temporal trends without relying on a specific case definition. The proposed framework was able to predict quite accurately the ILI trend of the forthcoming influenza season based only on the available information of the previous years. Moreover, we assessed the generalisability of the approach by evaluating its potentials for the detection of gastrointestinal syndromes. We evaluated the approach against the traditional surveillance data and despite the limited amount of data, the gastrointestinal trend was successfully detected. The result is a real-time flexible surveillance and prediction tool that is not constrained by any disease case definition.

epidemiology↗

bioRxiv2018

A systematic review of social contact surveys to inform transmission models of close contact infections

Social contact data are increasingly being used to inform models for infectious disease spread with the aim of guiding effective policies on disease prevention and control. In this paper, we undertake a systematic review of the study design, statistical analyses and outcomes of the many social contact surveys that have been published. Our primary focus is to identify the designs that have worked best and the most important determinants and to highlight the most robust [fi]ndings.\n\nTwo publicly accessible online databases were systematically searched for articles regarding social contact surveys. PRISMA guidelines were followed as closely as possible. In total, 64 social contact surveys were identi[fi]ed. These surveys were conducted in 24 countries, and more than 80% of the surveys were conducted in high-income countries. Study settings included general population (58%), schools/universities (37%) and health care/conference/research institutes (5%). The majority of studies did not focus on a speci[fi]c age group (38%), whereas others focused on adults (32%) or children (19%). Retrospective and prospective designs were used mostly (45% and 41% of the surveys, respectively) with 6% using both for comparison purposes. The de[fi]nition of a contact varied among surveys, e.g. a non-physical contact may require conversation, close proximity or both. Age, time schedule (e.g., weekday/weekend) and household size were identi[fi]ed as relevant determinants for contact pattern across a large number of studies. The surveys present a wide range of study designs. Throughout, we found that the overall contact patterns were remarkably robust for the study details. By considering the most common approach in each aspect of design (e.g., sampling schemes, data collection, de[fi]nition of contact), we could identify a common practice approach that can be used to facilitate comparison between studies and for benchmarking future studies.

epidemiology↗

bioRxiv2018

Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji

Dengue is a major health burden, but it can be challenging to examine transmission dynamics and evaluate control measures because outbreaks depend on multiple factors, including human population structure, prior immunity and climate. We combined population-representative paired sera collected before and after the major 2013/14 dengue-3 outbreak in Fiji with surveillance data to determine how such factors influence dengue virus transmission and control in island settings. Our results suggested the 10-19 year-old age group had the highest risk of acquiring infection, but we did not find strong evidence that other demographic or environmental risk factors were linked to seroconversion. Mathematical modelling showed that temperature-driven variation in transmission and herd immunity could not fully explain observed dynamics. However, there was evidence of an additional reduction in transmission coinciding with a vector clean-up campaign, which may have contributed to the decline in cases and prevented transmission continuing into the following season.

epidemiology↗