Epidemiological and ecological determinants of Zika virus transmission in an urban setting

Lourenço, José; Lima, Maricélia Maia de; Faria, Nuno Rodrigues; Walker, Andrew; Kraemer, Moritz U. G.; Villabona-Arenas, Christian Julián; Lambert, Ben; Cerqueira, Erenilde Marques de; Pybus, Oliver G.; Alcântara, Luíz Carlos Júnior; Recker, Mario

doi:10.7554/elife.29820

Cited by 87 publications

(80 citation statements)

References 78 publications

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“…More precisely, a parameter µ i , λ i,j is periodic iff it is a function of temperature T , which is periodic (with period one year). The parameter values infered from observed epidemiological dynamics agree very well among the three studies we used Lourenço et al [2017], Suparit et al [2018], . All the parameter values used in our models are summed up in Table 1.…”

Section: A Vector Borne Disease : Zika Virussupporting

confidence: 66%

“…We want to determine the probability of emergence of Zika Virus, a newly emerging vector borne disease of humans. Our starting point is the epidemioloical model of Zika used in previous studies Lourenço et al [2017], Suparit et al [2018], . The epidemiological dynamics in the human population is described by an SEIR model : susceptible individuals S H , exposed indivuals E H , infected individuals I H and recovered/removed individuals R H .…”

Section: A Vector Borne Disease : Zika Virusmentioning

confidence: 99%

See 1 more Smart Citation

Winter is coming: pathogen emergence in seasonal environments

Carmona

Gandon

2019

Preprint

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Many infectious diseases exhibit seasonal dynamics driven by periodic fluctuations of the environment. Predicting the risk of pathogen emergence at different points in time is key for the development of effective public health strategies. Here we study the impact of seasonality on the probability of emergence of directly transmitted pathogens under different epidemiological scenarios. We show that when the period of the fluctuation is large relative to the duration of the infection, the probability of emergence varies dramatically with the time at which the pathogen is introduced in the host population. In particular, we identify a new effect of seasonality (the winter is coming effect) where the probability of emergence is vanishingly small even though pathogen transmission is high. We use this theoretical framework to compare the impact of different control strategies on the average probability of emergence. We show that, when pathogen eradication is not attainable, the optimal strategy is to act intensively in a narrow time interval. Interestingly, the optimal control strategy is not always the strategy minimizing R 0 , the basic reproduction ratio of the pathogen. This theoretical framework is extended to study the probability of emergence of vector borne diseases in seasonal environments and we show how it can be used to improve risk maps of Zika virus emergence.

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Section: A Vector Borne Disease : Zika Virussupporting

confidence: 66%

Section: A Vector Borne Disease : Zika Virusmentioning

confidence: 99%

Winter is coming: pathogen emergence in seasonal environments

Carmona

Gandon

2019

Preprint

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“…Model output on cumulative death counts ( ) is fitted to the reported time series of deaths Λ (see Data) using a Bayesian MCMC approach previously implemented in other modelling studies [7][8][9][10] . Model variables are summarized in probability of dying with severe disease θ Gaussian distribution G(M=0.14, SD=0.007) [1,2,11,17] proportion of population at risk of severe disease ρ Gamma distribution G1(S=5, R=5/0.01), G2(S=5, R=5/0.001) --population size N UK 66.87M, Italy 60M ---…”

Section: Modelmentioning

confidence: 99%

Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic

Lourenço

Paton

Thompson

et al. 2020

Preprint

Self Cite

213

269

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The spread of a novel pathogenic infectious agent eliciting protective immunity is typically characterised by three distinct phases: (I) an initial phase of slow accumulation of new infections (often undetectable), (II) a second phase of rapid growth in cases of infection, disease and death, and (III) an eventual slow down of transmission due to the depletion of susceptible individuals, typically leading to the termination of the (first) epidemic wave. Before the implementation of control measures (e.g. social distancing, travel bans, etc) and under the assumption that infection elicits protective immunity, epidemiological theory indicates that the ongoing epidemic of SARS-CoV-2 will conform to this pattern. Here, we calibrate a susceptible-infected-recovered (SIR) model to data on cumulative reported SARS-CoV-2 associated deaths from the United Kingdom (UK) and Italy under the assumption that such deaths are well reported events that occur only in a vulnerable fraction of the population. We focus on model solutions which take into consideration previous estimates of critical epidemiological parameters such as the basic reproduction number (R0), probability of death in the vulnerable fraction of the population, infectious period and time from infection to death, with the intention of exploring the sensitivity of the system to the actual fraction of the population vulnerable to severe disease and death. Our simulations are in agreement with other studies that the current epidemic wave in the UK and Italy in the absence of interventions should have an approximate duration of 2-3 months, with numbers of deaths lagging behind in time relative to overall infections. Importantly, the results we present here suggest the ongoing epidemics in the UK and Italy started at least a month before the first reported death and have already led to the accumulation of significant levels of herd immunity in both countries. There is an inverse relationship between the proportion currently immune and the fraction of the population vulnerable to severe disease. This relationship can be used to determine how many people will require hospitalisation (and possibly die) in the coming weeks if we are able to accurately determine current levels of herd immunity. There is thus an urgent need for investment in technologies such as virus (or viral pseudotype) neutralization assays and other robust assays which provide reliable read-outs of protective immunity, and for the provision of open access to valuable data sources such as blood banks and paired samples of acute and convalescent sera from confirmed cases of SARS-CoV-2 to validate these. Urgent development and assessment of such tests should be followed by rapid implementation at scale to provide real-time data. These data will be critical to the proper assessment of the effects of social distancing and other measures currently being adopted to slow down the case incidence and for informing future policy direction.

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“…134 Recent modeling work corroborates these findings at the city-scale; namely that climatic conditions were optimal for ZIKV transmission in Feira de Santana, Brazil in 2015-16. 135 Another study highlights the worsening additional effect of an earthquake that hit Ecuador in 2016. 136 Importantly, Muñoz and colleagues utilized a similar R 0 model driven by operational seasonal climate forecasts to show that the ZIKV epidemic could have been theoretically forecast one month in advance in Brazil in 2015.…”

Section: Malariamentioning

confidence: 99%

Impact of recent and future climate change on vector‐borne diseases

Caminade

McIntyre

Jones

2018

Annals of the New York Academy of Sciences

473

282

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Climate change is one of the greatest threats to human health in the 21st century. Climate directly impacts health through climatic extremes, air quality, sea-level rise, and multifaceted influences on food production systems and water resources. Climate also affects infectious diseases, which have played a significant role in human history, impacting the rise and fall of civilizations and facilitating the conquest of new territories. Our review highlights significant regional changes in vector and pathogen distribution reported in temperate, peri-Arctic, Arctic, and tropical highland regions during recent decades, changes that have been anticipated by scientists worldwide. Further future changes are likely if we fail to mitigate and adapt to climate change. Many key factors affect the spread and severity of human diseases, including mobility of people, animals, and goods; control measures in place; availability of effective drugs; quality of public health services; human behavior; and political stability and conflicts. With drug and insecticide resistance on the rise, significant funding and research efforts must to be maintained to continue the battle against existing and emerging diseases, particularly those that are vector borne.

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Epidemiological and ecological determinants of Zika virus transmission in an urban setting

Cited by 87 publications

References 78 publications

Winter is coming: pathogen emergence in seasonal environments

Winter is coming: pathogen emergence in seasonal environments

Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic

Impact of recent and future climate change on vector‐borne diseases

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