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Wastewater sampling for the detection and monitoring of SARS-CoV-2 has been developed and applied at an unprecedented pace, however uncertainty remains when interpreting the measured viral RNA signals and their spatiotemporal variation. The proliferation of measurements that are below a quantifiable threshold, usually during non-endemic periods, poses a further challenge to interpretation and time-series analysis of the data. Inspired by research in the use of a custom Kalman smoother model to estimate the true level of SARS-CoV-2 RNA concentrations in wastewater, we propose an alternative left-censored dynamic linear model. Cross-validation of both models alongside a simple moving average, using data from 286 sewage treatment works across England, allows for a comprehensive validation of the proposed approach. The presented dynamic linear model is more parsimonious, has a faster computational time and is represented by a more flexible modelling framework than the equivalent Kalman smoother. Furthermore we show how the use of wastewater data, transformed by such models, correlates more closely with regional case rate positivity as published by the Office for National Statistics (ONS) Coronavirus (COVID-19) Infection Survey. The modelled output is more robust and is therefore capable of better complementing traditional surveillance than untransformed data or a simple moving average, providing additional confidence and utility for public health decision making. La détection et la surveillance du SARS-CoV-2 dans les eaux usées ont été développées et réalisées à un rythme sans précédent, mais l'interprétation des mesures de concentrations en ARN viral, et de leurs variations spatio-temporelles, pose question. En particulier, l'importante proportion de mesures en deçà du seuil de quantification, généralement pendant les périodes non endémiques, constitue un défi pour l'analyse de ces séries temporelles. Inspirés par un travail de recherche ayant produit un lisseur de Kalman adapté pour estimer les concentrations réelles en ARN de SARS-CoV-2 dans les eaux usées à partir de ce type de données, nous proposons un nouveau modèle linéaire dynamique avec censure à gauche. Une validation croisée de ces lisseurs, ainsi que d'un simple lissage par moyenne glissante, sur des données provenant de 286 stations d'épuration couvrant l'Angleterre, valide de façon complète l'approche proposée. Le modèle présenté est plus parcimonieux, offre un cadre de modélisation plus flexible et nécessite un temps de calcul réduit par rapport au Lisseur de Kalman équivalent. Les données issues des eaux usées ainsi lissées sont en outre plus fortement corrélées avec le taux d'incidence régional produit par le bureau des statistiques nationales (ONS) Coronavirus Infection Survey. Elles se montrent plus robustes que les données brutes, ou lissées par simple moyenne glissante, et donc plus à même de compléter la surveillance traditionnelle, renforçant ainsi la confiance en l'épidémiologie fondée sur les eaux usées et son utilité pour la prise de décisions de santé publique.

Wastewater surveillance could provide a means of monitoring SARS-CoV-2 prevalence that does not rely on testing individuals. Here, the authors report results from England’s national wastewater surveillance program, use it to estimate prevalence, and compare estimates with those from population-based prevalence surveys.

Abstract Background To reduce the coronavirus disease burden in England, along with many other countries, the government implemented a package of non-pharmaceutical interventions (NPIs) that have also impacted other transmissible infectious diseases such as norovirus. It is unclear what future norovirus disease incidence is likely to look like upon lifting these restrictions. Methods Here we use a mathematical model of norovirus fitted to community incidence data in England to project forward expected incidence based on contact surveys that have been collected throughout 2020–2021. Results We report that susceptibility to norovirus infection has likely increased between March 2020 and mid-2021. Depending upon assumptions of future contact patterns incidence of norovirus that is similar to pre-pandemic levels or an increase beyond what has been previously reported is likely to occur once restrictions are lifted. Should adult contact patterns return to 80% of pre-pandemic levels, the incidence of norovirus will be similar to previous years. If contact patterns return to pre-pandemic levels, there is a potential for the expected annual incidence to be up to 2-fold larger than in a typical year. The age-specific incidence is similar across all ages. Conclusions Continued national surveillance for endemic diseases such as norovirus will be essential after NPIs are lifted to allow healthcare services to adequately prepare for a potential increase in cases and hospital pressures beyond what is typically experienced.

ABSTRACT Understanding the complex interactions between virus and host that drive new strain evolution is key to predicting the emergence potential of variants and informing vaccine development. Under our hypothesis, future dominant human norovirus GII.4 variants with critical antigenic properties that allow them to spread are currently circulating undetected, having diverged years earlier. Through large-scale sequencing of GII.4 surveillance samples, we identified two variants with extensive divergence within domains that mediate neutralizing antibody binding. Subsequent serological characterization of these strains using temporally resolved adult and child sera suggests that neither candidate could spread globally in adults with multiple GII.4 exposures, yet young children with minimal GII.4 exposure appear susceptible. Antigenic cartography of surveillance and outbreak sera indicates that continued population exposure to GII.4 Sydney 2012 and antigenically related variants over a 6-year period resulted in a broadening of immunity to heterogeneous GII.4 variants, including those identified here. We show that the strongest antibody responses in adults exposed to GII.4 Sydney 2012 are directed to previously circulating GII.4 viruses. Our data suggest that the broadening of antibody responses compromises establishment of strong GII.4 Sydney 2012 immunity, thereby allowing the continued persistence of GII.4 Sydney 2012 and modulating the cycle of norovirus GII.4 variant replacement. Our results indicate a cycle of norovirus GII.4 variant replacement dependent upon population immunity. Young children are susceptible to divergent variants; therefore, emergence of these strains worldwide is driven proximally by changes in adult serological immunity and distally by viral evolution that confers fitness in the context of immunity. IMPORTANCE In our model, preepidemic human norovirus variants harbor genetic diversification that translates into novel antigenic features without compromising viral fitness. Through surveillance, we identified two viruses fitting this profile, forming long branches on a phylogenetic tree. Neither evades current adult immunity, yet young children are likely susceptible. By comparing serological responses, we demonstrate that population immunity varies by age/exposure, impacting predicted susceptibility to variants. Repeat exposure to antigenically similar variants broadens antibody responses, providing immunological coverage of diverse variants but compromising response to the infecting variant, allowing continued circulation. These data indicate norovirus GII.4 variant replacement is driven distally by virus evolution and proximally by immunity in adults.

Abstract Background The COVID-19 pandemic has disrupted the delivery of immunisation services globally. Many countries have postponed vaccination campaigns out of concern about infection risks to the staff delivering vaccination, the children being vaccinated, and their families. The World Health Organization recommends considering both the benefit of preventive campaigns and the risk of SARS-CoV-2 transmission when making decisions about campaigns during COVID-19 outbreaks, but there has been little quantification of the risks. Methods We modelled excess SARS-CoV-2 infection risk to vaccinators, vaccinees, and their caregivers resulting from vaccination campaigns delivered during a COVID-19 epidemic. Our model used population age structure and contact patterns from three exemplar countries (Burkina Faso, Ethiopia, and Brazil). It combined an existing compartmental transmission model of an underlying COVID-19 epidemic with a Reed-Frost model of SARS-CoV-2 infection risk to vaccinators and vaccinees. We explored how excess risk depends on key parameters governing SARS-CoV-2 transmissibility, and aspects of campaign delivery such as campaign duration, number of vaccinations, and effectiveness of personal protective equipment (PPE) and symptomatic screening. Results Infection risks differ considerably depending on the circumstances in which vaccination campaigns are conducted. A campaign conducted at the peak of a SARS-CoV-2 epidemic with high prevalence and without special infection mitigation measures could increase absolute infection risk by 32 to 45% for vaccinators and 0.3 to 0.5% for vaccinees and caregivers. However, these risks could be reduced to 3.6 to 5.3% and 0.1 to 0.2% respectively by use of PPE that reduces transmission by 90% (as might be achieved with N95 respirators or high-quality surgical masks) and symptomatic screening. Conclusions SARS-CoV-2 infection risks to vaccinators, vaccinees, and caregivers during vaccination campaigns can be greatly reduced by adequate PPE, symptomatic screening, and appropriate campaign timing. Our results support the use of adequate risk mitigation measures for vaccination campaigns held during SARS-CoV-2 epidemics, rather than cancelling them entirely.

Abstract Background Release of virus-blocking Wolbachia-infected mosquitoes is an emerging disease control strategy that aims to control dengue and other arboviral infections. Early entomological data and modelling analyses have suggested promising outcomes, and wMel Wolbachia releases are now ongoing or planned in 12 countries. To help inform government, donor, or philanthropist decisions on scale-up beyond single city releases, we assessed this technology’s cost-effectiveness under alternative programmatic options. Methods Using costing data from existing Wolbachia releases, previous dynamic model-based estimates of Wolbachia effectiveness, and a spatially explicit model of release and surveillance requirements, we predicted the costs and effectiveness of the ongoing programme in Yogyakarta City and three new hypothetical programmes in Yogyakarta Special Autonomous Region, Jakarta, and Bali. Results We predicted Wolbachia to be a highly cost-effective intervention when deployed in high-density urban areas with gross cost-effectiveness below $1500 per DALY averted. When offsets from the health system and societal perspective were included, such programmes even became cost saving over 10-year time horizons with favourable benefit-cost ratios of 1.35 to 3.40. Sequencing Wolbachia releases over 10 years could reduce programme costs by approximately 38% compared to simultaneous releases everywhere, but also delays the benefits. Even if unexpected challenges occurred during deployment, such as emergence of resistance in the medium-term or low effective coverage, Wolbachia would remain a cost-saving intervention. Conclusions Wolbachia releases in high-density urban areas are expected to be highly cost-effective and could potentially be the first cost-saving intervention for dengue. Sites with strong public health infrastructure, fiscal capacity, and community support should be prioritised.

Abstract Background Wolbachia-infected mosquitoes reduce dengue virus transmission, and city-wide releases in Yogyakarta city, Indonesia, are showing promising entomological results. Accurate estimates of the burden of dengue, its spatial distribution and the potential impact of Wolbachia are critical in guiding funder and government decisions on its future wider use. Methods Here, we combine multiple modelling methods for burden estimation to predict national case burden disaggregated by severity and map the distribution of burden across the country using three separate data sources. An ensemble of transmission models then predicts the estimated reduction in dengue transmission following a nationwide roll-out of wMel Wolbachia. Results We estimate that 7.8 million (95% uncertainty interval [UI] 1.8–17.7 million) symptomatic dengue cases occurred in Indonesia in 2015 and were associated with 332,865 (UI 94,175–754,203) lost disability-adjusted life years (DALYs). The majority of dengue’s burden was due to non-severe cases that did not seek treatment or were challenging to diagnose in outpatient settings leading to substantial underreporting. Estimated burden was highly concentrated in a small number of large cities with 90% of dengue cases occurring in 15.3% of land area. Implementing a nationwide Wolbachia population replacement programme was estimated to avert 86.2% (UI 36.2–99.9%) of cases over a long-term average. Conclusions These results suggest interventions targeted to the highest burden cities can have a disproportionate impact on dengue burden. Area-wide interventions, such as Wolbachia, that are deployed based on the area covered could protect people more efficiently than individual-based interventions, such as vaccines, in such dense environments.

In this introduction to the Special Issue on methods for modelling of infectious disease epidemiology we provide a commentary and overview of the field. We suggest that the field has been through three revolutions that have focussed on specific methodological developments; disease dynamics and heterogeneity, advanced computing and inference, and complexity and application to the real-world. Infectious disease dynamics and heterogeneity dominated until the 1980s where the use of analytical models illustrated fundamental concepts such as herd immunity. The second revolution embraced the integration of data with models and the increased use of computing. From the turn of the century an emergence of novel datasets enabled improved modelling of real-world complexity. The emergence of more complex data that reflect the real-world heterogeneities in transmission resulted in the development of improved inference methods such as particle filtering. Each of these three revolutions have always kept the understanding of infectious disease spread as its motivation but have been developed through the use of new techniques, tools and the availability of data. We conclude by providing a commentary on what the next revoluition in infectious disease modelling may be.

Abstract Background Zika virus (ZIKV) emerged in Latin America and the Caribbean (LAC) region in 2013, with 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 the lack of a comprehensive collation of data from affected countries. Methods 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 90 major cities within 35 countries. Seasonality was determined by spatio-temporal estimates of Aedes aegypti vectorial 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. Results 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 would present 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

Abstract Background To support poliomyelitis eradication in Pakistan, environmental surveillance (ES) of wastewater has been expanded alongside surveillance for acute flaccid paralysis (AFP). ES is a relatively new method of surveillance, and the population sensitivity of detecting poliovirus within endemic settings requires estimation. Methods Data for wild serotype 1 poliovirus from AFP and ES from January 2011 to September 2015 from 14 districts in Pakistan were analysed using a multi-state model framework. This framework was used to estimate the sensitivity of poliovirus detection from each surveillance source and parameters such as the duration of infection within a community. Results The location and timing of poliomyelitis cases showed spatial and temporal variability. The sensitivity of AFP surveillance to detect serotype 1 poliovirus infection in a district and its neighbours per month was on average 30.0% (95% CI 24.8–35.8) and increased with the incidence of poliomyelitis cases. The average population sensitivity of a single environmental sample was 59.4% (95% CI 55.4–63.0), with significant variation in site-specific estimates (median varied from 33.3–79.2%). The combined population sensitivity of environmental and AFP surveillance in a given month was on average 98.1% (95% CI 97.2–98.7), assuming four samples per month for each site. Conclusions ES can be a highly sensitive supplement to AFP surveillance in areas with converging sewage systems. As ES for poliovirus is expanded, it will be important to identify factors associated with variation in site sensitivity, leading to improved site selection and surveillance system performance.

Abstract Background The international spread of wild poliomyelitis outbreaks continues to threaten eradication of poliomyelitis and in 2014 a public health emergency of international concern was declared. Here we describe a risk scoring system that has been used to assess country-level risks of wild poliomyelitis outbreaks, to inform prioritisation of mass vaccination planning, and describe the change in risk from 2014 to 2016. The methods were also used to assess the risk of emergence of vaccine-derived poliomyelitis outbreaks. Methods Potential explanatory variables were tested against the reported outbreaks of wild poliomyelitis since 2003 using multivariable regression analysis. The regression analysis was translated to a risk score and used to classify countries as Low, Medium, Medium High and High risk, based on the predictive ability of the score. Results Indicators of population immunity, population displacement and diarrhoeal disease were associated with an increased risk of both wild and vaccine-derived outbreaks. High migration from countries with wild cases was associated with wild outbreaks. High birth numbers were associated with an increased risk of vaccine-derived outbreaks. Conclusions Use of the scoring system is a transparent and rapid approach to assess country risk of wild and vaccine-derived poliomyelitis outbreaks. Since 2008 there has been a steep reduction in the number of wild poliomyelitis outbreaks and the reduction in countries classified as High and Medium High risk has reflected this. The risk of vaccine-derived poliomyelitis outbreaks has varied geographically. These findings highlight that many countries remain susceptible to poliomyelitis outbreaks and maintenance or improvement in routine immunisation is vital.

Zika Preparedness Latin American Network (ZikaPLAN) is a research consortium funded by the European Commission to address the research gaps in combating Zika and to establish a sustainable network with research capacity building in the Americas. Here we present a report on ZikaPLAN`s mid-term achievements since its initiation in October 2016 to June 2019, illustrating the research objectives of the 15 work packages ranging from virology, diagnostics, entomology and vector control, modelling to clinical cohort studies in pregnant women and neonates, as well as studies on the neurological complications of Zika infections in adolescents and adults. For example, the Neuroviruses Emerging in the Americas Study (NEAS) has set up more than 10 clinical sites in Colombia. Through the Butantan Phase 3 dengue vaccine trial, we have access to samples of 17,000 subjects in 14 different geographic locations in Brazil. To address the lack of access to clinical samples for diagnostic evaluation, ZikaPLAN set up a network of quality sites with access to well-characterized clinical specimens and capacity for independent evaluations. The International Committee for Congenital Anomaly Surveillance Tools was formed with global representation from regional networks conducting birth defects surveillance. We have collated a comprehensive inventory of resources and tools for birth defects surveillance, and developed an App for low resource regions facilitating the coding and description of all major externally visible congenital anomalies including congenital Zika syndrome. Research Capacity Network (REDe) is a shared and open resource centre where researchers and health workers can access tools, resources and support, enabling better and more research in the region. Addressing the gap in research capacity in LMICs is pivotal in ensuring broad-based systems to be prepared for the next outbreak. Our shared and open research space through REDe will be used to maximize the transfer of research into practice by summarizing the research output and by hosting the tools, resources, guidance and recommendations generated by these studies. Leveraging on the research from this consortium, we are working towards a research preparedness network.

We know very little about physiological constraints on the evolution of life-history traits in general, and, in particular, about physiological and molecular adjustments that accompany the evolution of variation in lifespan. Identifying mechanisms that underlie adaptive variation in lifespan should provide insight into the evolution of trade-offs between lifespan and other life-history traits. Telomeres, the DNA caps at the ends of linear chromosomes, usually shorten as animals age, but whether telomere rate of change is associated with lifespan is unknown. We measured telomere length in erythrocytes from five bird species with markedly different lifespans. Species with shorter lifespans lost more telomeric repeats with age than species with longer lifespans. A similar correlation is seen in mammals. Furthermore, telomeres did not shorten with age in Leach's storm-petrels, an extremely long-lived bird, but actually lengthened. This novel finding suggests that regulation of telomere length is associated not only with cellular replicative lifespan, but also with organismal lifespan, and that very long-lived organisms have escaped entirely any telomeric constraint on cellular replicative lifespan. [ABSTRACT FROM AUTHOR]

Background: Circulating vaccine derived poliovirus (cVDPV) outbreaks remain a threat to polio eradication. To reduce cases of polio from cVDPV of serotype 2, the serotype 2 component of the vaccine has been removed from the global vaccine supply, but outbreaks of cVDPV2 have continued. The objective of this work is to understand the factors associated with later detection in order to improve detection of these unwanted events. Methods: The number of nucleotide differences between each cVDPV outbreak and the oral polio vaccine (OPV) strain was used to approximate the time from emergence to detection. Only independent emergences were included in the analysis. Variables such as serotype, surveillance quality, and World Health Organization (WHO) region were tested in a negative binomial regression model to ascertain whether these variables were associated with higher nucleotide differences upon detection. Results: In total, 74 outbreaks were analysed from 24 countries between 2004-2019. For serotype 1 (n=10), the median time from seeding until outbreak detection was 572 (95% uncertainty interval (UI) 279-2016), for serotype 2 (n=59), 276 (95% UI 172-765) days, and for serotype 3 (n=5), 472 (95% UI 392-603) days. Significant improvement in the time to detection was found with increasing surveillance of non-polio acute flaccid paralysis (AFP) and adequate stool collection. Conclusions: cVDPVs remain a risk; all WHO regions have reported at least one VDPV outbreak since the first outbreak in 2000 and outbreak response campaigns using monovalent OPV type 2 risk seeding future outbreaks. Maintaining surveillance for poliomyelitis after local elimination is essential to quickly respond to both emergence of VDPVs and potential importations as low-quality AFP surveillance causes outbreaks to continue undetected. Considerable variation in the time between emergence and detection of VDPVs were apparent, and other than surveillance quality and inclusion of environmental surveillance, the reasons for this remain unclear.

Background: Circulating vaccine derived poliovirus (cVDPV) outbreaks remain a threat to polio eradication. To reduce cases of polio from cVDPV of serotype 2, the serotype 2 component of the vaccine has been removed from the global vaccine supply, but outbreaks of cVDPV2 have continued. The objective of this work is to understand the factors associated with later detection in order to improve detection of these unwanted events. Methods: The number of nucleotide differences between each cVDPV outbreak and the oral polio vaccine (OPV) strain was used to approximate the time from emergence to detection. Only independent emergences were included in the analysis. Variables such as serotype, surveillance quality, and World Health Organization (WHO) region were tested in a negative binomial regression model to ascertain whether these variables were associated with higher nucleotide differences upon detection. Results: In total, 74 outbreaks were analysed from 24 countries between 2004-2019. For serotype 1 (n=10), the median time from seeding until outbreak detection was 284 (95% uncertainty interval (UI) 284-2008) days, for serotype 2 (n=59), 276 (95% UI 172-765) days, and for serotype 3 (n=5), 472 (95% UI 392-603) days. Significant improvement in the time to detection was found with increasing surveillance of non-polio acute flaccid paralysis (AFP) and adequate stool collection. Conclusions: cVDPVs remain a risk; all WHO regions have reported at least one VDPV outbreak since the first outbreak in 2000 and outbreak response campaigns using monovalent OPV type 2 risk seeding future outbreaks. Maintaining surveillance for poliomyelitis after local elimination is essential to quickly respond to both emergence of VDPVs and potential importations as low-quality AFP surveillance causes outbreaks to continue undetected. Considerable variation in the time between emergence and detection of VDPVs were apparent, and other than surveillance quality and inclusion of environmental surveillance, the reasons for this remain unclear.

Background: Circulating vaccine derived poliovirus (cVDPV) outbreaks remain a threat to polio eradication. To reduce cases of polio from cVDPV of serotype 2, the serotype 2 component of the vaccine has been removed from the global vaccine supply, but outbreaks of cVDPV2 have continued. The objective of this work is to understand the factors associated with later detection in order to improve detection of these unwanted events. Methods: The number of nucleotide differences between each cVDPV outbreak and the oral polio vaccine (OPV) strain was used to approximate the time from emergence to detection. Only independent emergences were included in the analysis. Variables such as serotype, surveillance quality, and World Health Organization (WHO) region were tested in a negative binomial regression model to ascertain whether these variables were associated with higher nucleotide differences upon detection. Results: In total, 74 outbreaks were analysed from 24 countries between 2004 and 2019. For serotype 1 (n=10), the median time from seeding until outbreak detection was 284 (95% uncertainty interval (UI) 284-2008) days, for serotype 2 (n=59), 276 (95% UI 172-765) days, and for serotype 3 (n=5), 472 (95% UI 392-603) days. Significant improvement in the time to detection was found with increasing surveillance of non-polio acute flaccid paralysis (AFP) and adequate stool collection. Conclusions: cVDPVs remain a risk globally; all WHO regions have reported at least one VDPV outbreak since the first outbreak in 2001. Maintaining surveillance for poliomyelitis after local elimination is essential to quickly respond to both emergence of VDPVs and potential importations. Considerable variation in the time between emergence and detection of VDPVs were apparent, and other than surveillance quality and inclusion of environmental surveillance, the reasons for this remain unclear.

Summary: Background: Temperature and rainfall patterns are known to influence seasonal patterns of dengue transmission. However, the effect of severe drought and extremely wet conditions on the timing and intensity of dengue epidemics is poorly understood. In this study, we aimed to quantify the non-linear and delayed effects of extreme hydrometeorological hazards on dengue risk by level of urbanisation in Brazil using a spatiotemporal model. Methods: We combined distributed lag non-linear models with a spatiotemporal Bayesian hierarchical model framework to determine the exposure-lag-response association between the relative risk (RR) of dengue and a drought severity index. We fit the model to monthly dengue case data for the 558 microregions of Brazil between January, 2001, and January, 2019, accounting for unobserved confounding factors, spatial autocorrelation, seasonality, and interannual variability. We assessed the variation in RR by level of urbanisation through an interaction between the drought severity index and urbanisation. We also assessed the effect of hydrometeorological hazards on dengue risk in areas with a high frequency of water supply shortages. Findings: The dataset included 12 895 293 dengue cases reported between 2001 and 2019 in Brazil. Overall, the risk of dengue increased between 0–3 months after extremely wet conditions (maximum RR at 1 month lag 1·56 [95% CI 1·41–1·73]) and 3–5 months after drought conditions (maximum RR at 4 months lag 1·43 [1·22–1·67]). Including a linear interaction between the drought severity index and level of urbanisation improved the model fit and showed the risk of dengue was higher in more rural areas than highly urbanised areas during extremely wet conditions (maximum RR 1·77 [1·32–2·37] at 0 months lag vs maximum RR 1·58 [1·39–1·81] at 2 months lag), but higher in highly urbanised areas than rural areas after extreme drought (maximum RR 1·60 [1·33–1·92] vs 1·15 [1·08–1·22], both at 4 months lag). We also found the dengue risk following extreme drought was higher in areas that had a higher frequency of water supply shortages. Interpretation: Wet conditions and extreme drought can increase the risk of dengue with different delays. The risk associated with extremely wet conditions was higher in more rural areas and the risk associated with extreme drought was exacerbated in highly urbanised areas, which have water shortages and intermittent water supply during droughts. These findings have implications for targeting mosquito control activities in poorly serviced urban areas, not only during the wet and warm season, but also during drought periods. Funding: Royal Society, Medical Research Council, Wellcome Trust, National Institutes of Health, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, and Conselho Nacional de Desenvolvimento Científico e Tecnológico. Translation: For the Portuguese translation of the abstract see Supplementary Materials section.

Pakistan currently provides a substantial challenge to global polio eradication, having contributed to 73% of reported poliomyelitis in 2015 and 54% in 2016. A better understanding of the risk factors and movement patterns that contribute to poliovirus transmission across Pakistan would support evidence-based planning for mass vaccination campaigns.We fit mixed-effects logistic regression models to routine surveillance data recording the presence of poliomyelitis associated with wild-type 1 poliovirus in districts of Pakistan over 6-month intervals between 2010 to 2016. To accurately capture the force of infection (FOI) between districts, we compared 6 models of population movement (adjacency, gravity, radiation, radiation based on population density, radiation based on travel times, and mobile-phone based). We used the best-fitting model (based on the Akaike Information Criterion [AIC]) to produce 6-month forecasts of poliomyelitis incidence. The odds of observing poliomyelitis decreased with improved routine or supplementary (campaign) immunisation coverage (multivariable odds ratio [OR] = 0.75, 95% confidence interval [CI] 0.67-0.84; and OR = 0.75, 95% CI 0.66-0.85, respectively, for each 10% increase in coverage) and increased with a higher rate of reporting non-polio acute flaccid paralysis (AFP) (OR = 1.13, 95% CI 1.02-1.26 for a 1-unit increase in non-polio AFP per 100,000 persons aged

Global withdrawal of serotype-2 oral poliovirus vaccine (OPV2) took place in April 2016. This marked a milestone in global polio eradication and was a public health intervention of unprecedented scale, affecting 155 countries. Achieving high levels of serotype-2 population immunity before OPV2 withdrawal was critical to avoid subsequent outbreaks of serotype-2 vaccine-derived polioviruses (VDPV2s).In August 2015, we estimated vaccine-induced population immunity against serotype-2 poliomyelitis for 1 January 2004-30 June 2015 and produced forecasts for April 2016 by district in Nigeria and Pakistan. Population immunity was estimated from the vaccination histories of children 70% population immunity among children

Phylogeographic methods aim to infer migration trends and the history of sampled lineages from genetic data. Applications of phylogeography are broad, and in the context of pathogens include the reconstruction of transmission histories and the origin and emergence of outbreaks. Phylogeographic inference based on bottom-up population genetics models is computationally expensive, and as a result faster alternatives based on the evolution of discrete traits have become popular. In this paper, we show that inference of migration rates and root locations based on discrete trait models is extremely unreliable and sensitive to biased sampling. To address this problem, we introduce BASTA (BAyesian STructured coalescent Approximation), a new approach implemented in BEAST2 that combines the accuracy of methods based on the structured coalescent with the computational efficiency required to handle more than just few populations. We illustrate the potentially severe implications of poor model choice for phylogeographic analyses by investigating the zoonotic transmission of Ebola virus. Whereas the structured coalescent analysis correctly infers that successive human Ebola outbreaks have been seeded by a large unsampled non-human reservoir population, the discrete trait analysis implausibly concludes that undetected human-to-human transmission has allowed the virus to persist over the past four decades. As genomics takes on an increasingly prominent role informing the control and prevention of infectious diseases, it will be vital that phylogeographic inference provides robust insights into transmission history.

We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known 'artificial behaviours' comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified.

Theory and observations suggest that offspring abandonment in animals may occur when the costs to future reproductive output of current reproductive effort outweigh the fitness benefits of rearing the current brood. While hormonal cues (i.e. corticosterone) or energy reserves are believed to be involved, few studies have directly focused on the proximate cues influencing behaviours directly related to reproductive success. To address this information gap, we determined the incubation metabolic rates and corticosterone (CORT) levels of naturally fasting and freely incubating ancient murrelets (Synthliboramphus antiquus). Respiratory quotient (RQ) increased with date, suggesting that incubating ancient murrelets shifted from strictly lipid-based metabolism towards more protein-based metabolism as incubation progressed. Birds that hatched only one nestling had higher levels of circulating CORT than those which hatched two, suggesting that birds which laid only a single egg found incubation more stressful than those which laid two. However, CORT levels and incubation shift lengths were not correlated, suggesting that birds that undertook prolonged incubation shifts did so only when their energy stores were not jeopardized.

Outbreaks of poliomyelitis in African countries that were previously free of wild-type poliovirus cost the Global Polio Eradication Initiative US$850 million during 2003-2009, and have limited the ability of the program to focus on endemic countries. A quantitative understanding of the factors that predict the distribution and timing of outbreaks will enable their prevention and facilitate the completion of global eradication.Children with poliomyelitis in Africa from 1 January 2003 to 31 December 2010 were identified through routine surveillance of cases of acute flaccid paralysis, and separate outbreaks associated with importation of wild-type poliovirus were defined using the genetic relatedness of these viruses in the VP1/2A region. Potential explanatory variables were examined for their association with the number, size, and duration of poliomyelitis outbreaks in 6-mo periods using multivariable regression analysis. The predictive ability of 6-mo-ahead forecasts of poliomyelitis outbreaks in each country based on the regression model was assessed. A total of 142 genetically distinct outbreaks of poliomyelitis were recorded in 25 African countries, resulting in 1-228 cases (median of two cases). The estimated number of people arriving from infected countries and