Reviewing estimates of the basic reproduction number for dengue, Zika and chikungunya across global climate zones

A scoping literature review of global dengue age-stratified seroprevalence data: estimating dengue force of infection in endemic countries

BACKGROUND

Dengue poses a significant burden worldwide, and a more comprehensive understanding of the heterogeneity in the intensity of dengue transmission within endemic countries is necessary to evaluate the potential impact of public health interventions.

METHODS

This scoping literature review aimed to update a previous study of dengue transmission intensity by collating global age-stratified dengue seroprevalence data published in the Medline, Embase and Web of Science databases from 2014 to 2023. These data were then utilised to calibrate catalytic models and estimate the force of infection (FOI), which is the yearly per-capita risk of infection for a typical susceptible individual.

FINDINGS

We found a total of 66 new publications containing 219 age-stratified seroprevalence datasets across 30 endemic countries. Together with the previously available average FOI estimates, there are now more than 250 dengue average FOI estimates obtained from seroprevalence studies from across the world.

INTERPRETATION

The results show large heterogeneities in average dengue FOI both across and within countries. These new estimates can be used to inform ongoing modelling efforts to improve our understanding of the drivers of the heterogeneity in dengue transmission globally, which in turn can help inform the optimal implementation of public health interventions.

FUNDING

UK Medical Research Council, Wellcome Trust, Community Jameel, Drugs for Neglected Disease initiative (DNDi) funded by the French Development Agency, Médecins Sans Frontières International; Swiss Agency for Development and Cooperation and UK aid.

Model-based estimates of chikungunya epidemiological parameters and outbreak risk from varied data types

Assessing the factors responsible for differences in outbreak severity for the same pathogen is a challenging task, since outbreak data are often incomplete and may vary in type across outbreaks (e.g., daily case counts, serology, cases per household). We propose that outbreaks described with varied data types can be directly compared by using those data to estimate a common set of epidemiological parameters. To demonstrate this for chikungunya virus (CHIKV), we developed a realistic model of CHIKV transmission, along with a Bayesian inference method that accommodates any type of outbreak data that can be simulated. The inference method makes use of the fact that all data types arise from the same transmission process, which is simulated by the model. We applied these tools to data from three real-world outbreaks of CHIKV in Italy, Cambodia, and Bangladesh to estimate nine model parameters. We found that these populations differed in several parameters, including pre-existing immunity and house-to-house differences in mosquito activity. These differences resulted in posterior predictions of local CHIKV transmission risk that varied nearly fourfold: 16% in Italy, 28% in Cambodia, and 62% in Bangladesh. Our inference method and model can be applied to improve understanding of the epidemiology of CHIKV and other pathogens for which outbreaks are described with varied data types.

Monolithic affinity columns in 3D printed microfluidics for chikungunya RNA detection

Mosquito-borne pathogens plague much of the world, yet rapid and simple diagnosis is not available for many affected patients. Using a custom stereolithography 3D printer, we created microfluidic devices with affinity monoliths that could retain, noncovalently attach a fluorescent tag, and detect oligonucleotide and viral RNA. We optimized the fluorescent binding and sample load times using an oligonucleotide sequence from chikungunya virus (CHIKV). We also tested the specificity of CHIKV capture relative to genetically similar Sindbis virus. Moreover, viral RNA from both viruses was flowed through capture columns to study the efficiency and specificity of the column for viral CHIKV. We detected ~107 loaded viral genome copies, which was similar to levels in clinical samples during acute infection. These results show considerable promise for development of this platform into a rapid mosquito-borne viral pathogen detection system.

Temporary Cross-Immunity as a Plausible Driver of Asynchronous Cycles of Dengue Serotypes

Many infectious diseases exist as multiple variants, with interactions between variants potentially driving epidemiological dynamics. These diseases include dengue, which infects hundreds of millions of people every year and exhibits complex multi-serotype dynamics. Antibodies produced in response to primary infection by one of the four dengue serotypes can produce a period of temporary cross-immunity (TCI) to infection by other serotypes. After this period, the remaining antibodies can facilitate the entry of heterologous serotypes into target cells, thus enhancing severity of secondary infection by a heterologous serotype. This represents antibody-dependent enhancement (ADE). In this study, we analyze an epidemiological model to provide novel insights into the importance of TCI and ADE in producing cyclic outbreaks of dengue serotypes. Our analyses reveal that without TCI, such cyclic outbreaks are synchronous across serotypes and only occur when ADE produces high transmission rates. In contrast, the presence of TCI allows asynchronous cycles of serotypes by inducing a time lag between recovery from primary infection by one serotype and secondary infection by another, with such cycles able to occur without ADE. Our results suggest that TCI is a fundamental driver of asynchronous cycles of dengue serotypes and possibly other multi-variant diseases.

Mechanical transmission of dengue virus by Aedes aegypti may influence disease transmission dynamics during outbreaks

BACKGROUND

Dengue virus outbreaks are increasing in number and severity worldwide. Viral transmission is assumed to require a minimum time period of viral replication within the mosquito midgut. It is unknown if alternative transmission periods not requiring replication are possible.

METHODS

We used a mouse model of dengue virus transmission to investigate the potential of mechanical transmission of dengue virus. We investigated minimal viral titres necessary for development of symptoms in bitten mice and used resulting parameters to inform a new model of dengue virus transmission within a susceptible population.

FINDINGS

Naïve mice bitten by mosquitoes immediately after they took partial blood meals from dengue infected mice showed symptoms of dengue virus, followed by mortality. Incorporation of mechanical transmission into mathematical models of dengue virus transmission suggest that this supplemental transmission route could result in larger outbreaks which peak sooner.

INTERPRETATION

The potential of dengue transmission routes independent of midgut viral replication has implications for vector control strategies that target mosquito lifespan and suggest the possibility of similar mechanical transmission routes in other disease-carrying mosquitoes.

FUNDING

This study was funded by grants from the National Health Research Institutes, Taiwan (04D2-MMMOST02), the Human Frontier Science Program (RGP0033/2021), the National Institutes of Health (1R01AI143698-01A1, R01AI151004 and DP2AI152071) and the Ministry of Science and Technology, Taiwan (MOST104-2321-B-400-016).

Investigation of the effects of temperature and relative humidity on the propagation of COVID-19 in different climatic zones

This study aims to evaluate the effects of temperature and relative humidity on the propagation of COVID-19 for indoor heating, ventilation, and air conditioning design and policy development in different climate zones. We proposed a cumulative lag model with two specific parameters of specific average temperature and specific relative humidity to evaluate the impact of temperature and relative humidity on COVID-19 transmission by calculating the relative risk of cumulative effect and the relative risk of lag effect. We considered the temperature and relative humidity corresponding to the relative risk of cumulative effect or the relative risk of lag effect equal to 1 as the thresholds of outbreak. In this paper, we took the overall relative risk of cumulative effect equal to 1 as the thresholds. Data on daily new confirmed cases of COVID-19 since January 1, 2021, to December 31, 2021, for three sites in each of four climate zones similar to cold, mild, hot summer and cold winter, and hot summer and warm winter were selected for this study. Temperature and relative humidity had a lagged effect on COVID-19 transmission, with peaking the relative risk of lag effect at a lag of 3-7 days for most regions. All regions had different parameters areas with the relative risk of cumulative effect greater than 1. The overall relative risk of cumulative effect was greater than 1 in all regions when specific relative humidity was higher than 0.4, and when specific average temperature was higher than 0.42. In areas similar to hot summer and cold winter, temperature and the overall relative risk of cumulative effect were highly monotonically positively correlated. In areas similar to hot summer and warm winter, there was a monotonically positive correlation between relative humidity and the overall relative risk of cumulative effect. This study provides targeted recommendations for indoor air and heating, ventilation, and air conditioning system control strategies and outbreak prevention strategies to reduce the risk of COVID-19 transmission. In addition, countries should combine vaccination and non-pharmaceutical control measures, and strict containment policies are beneficial to control another pandemic of COVID-19 and similar viruses.

Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R 0 for the Republic of Panama in the 1999-2022 period

Nowadays, the ability to make data-driven decisions in public health is of utmost importance. To achieve this, it is necessary for modelers to comprehend the impact of models on the future state of healthcare systems. Compartmental models are a valuable tool for making informed epidemiological decisions, and the proper parameterization of these models is crucial for analyzing epidemiological events. This work evaluated the use of compartmental models in conjunction with Particle Swarm Optimization (PSO) to determine optimal solutions and understand the dynamics of Dengue epidemics. The focus was on calculating and evaluating the rate of case reproduction, R 0 , for the Republic of Panama. Three compartmental models were compared: Susceptible-Infected-Recovered (SIR), Susceptible-Exposed-Infected-Recovered (SEIR), and Susceptible-Infected-Recovered Human-Susceptible-Infected Vector (SIR Human-SI Vector, SIR-SI). The models were informed by demographic data and Dengue incidence in the Republic of Panama between 1999 and 2022, and the susceptible population was analyzed. The SIR, SEIR, and SIR-SI models successfully provided R 0 estimates ranging from 1.09 to 1.74. This study provides, to the best of our understanding, the first calculation of R 0 for Dengue outbreaks in the Republic of Panama.

Long-term projections of the impacts of warming temperatures on Zika and dengue risk in four Brazilian cities using a temperature-dependent basic reproduction number

For vector-borne diseases the basic reproduction number [Formula: see text], a measure of a disease's epidemic potential, is highly temperature-dependent. Recent work characterizing these temperature dependencies has highlighted how climate change may impact geographic disease spread. We extend this prior work by examining how newly emerging diseases, like Zika, will be impacted by specific future climate change scenarios in four diverse regions of Brazil, a country that has been profoundly impacted by Zika. We estimated a [Formula: see text], derived from a compartmental transmission model, characterizing Zika (and, for comparison, dengue) transmission potential as a function of temperature-dependent biological parameters specific to Aedes aegypti. We obtained historical temperature data for the five-year period 2015-2019 and projections for 2045-2049 by fitting cubic spline interpolations to data from simulated atmospheric data provided by the CMIP-6 project (specifically, generated by the GFDL-ESM4 model), which provides projections under four Shared Socioeconomic Pathways (SSP). These four SSP scenarios correspond to varying levels of climate change severity. We applied this approach to four Brazilian cities (Manaus, Recife, Rio de Janeiro, and São Paulo) that represent diverse climatic regions. Our model predicts that the [Formula: see text] for Zika peaks at 2.7 around 30°C, while for dengue it peaks at 6.8 around 31°C. We find that the epidemic potential of Zika will increase beyond current levels in Brazil in all of the climate scenarios. For Manaus, we predict that the annual [Formula: see text] range will increase from 2.1-2.5, to 2.3-2.7, for Recife we project an increase from 0.4-1.9 to 0.6-2.3, for Rio de Janeiro from 0-1.9 to 0-2.3, and for São Paulo from 0-0.3 to 0-0.7. As Zika immunity wanes and temperatures increase, there will be increasing epidemic potential and longer transmission seasons, especially in regions where transmission is currently marginal. Surveillance systems should be implemented and sustained for early detection.

Expected endpoints from future chikungunya vaccine trial sites informed by serological data and modeling

In recent decades, there has been an increased interest in developing a vaccine for chikungunya. However, due to its unpredictable transmission, planning for a chikungunya vaccine trial is challenging. To inform decision making on the selection of sites for a vaccine efficacy trial, we developed a new framework for projecting the expected number of endpoint events at a given site. In this framework, we first accounted for population immunity using serological data collated from a systematic review and used it to estimate parameters related to the timing and size of past outbreaks, as predicted by an SIR transmission model. Then, we used that model to project the infection attack rate of a hypothetical future outbreak, in the event that one were to occur at the time of a future trial. This informed projections of how many endpoint events could be expected if a trial were to take place at that site. Our results suggest that some sites may have sufficient transmission potential and susceptibility to support future vaccine trials, in the event that an outbreak were to occur at those sites. In general, we conclude that sites that have experienced outbreaks within the past 10 years may be poorer targets for chikungunya vaccine efficacy trials in the near future. Our framework also generates projections of the numbers of endpoint events by age, which could inform study participant recruitment efforts.

Isolation in the control of epidemic

Among many epidemic prevention measures, isolation is an important method to control the spread of infectious disease. Scholars rarely study the impact of isolation on disease dissemination from a quantitative perspective. In this paper, we introduce an isolation ratio and establish the corresponding model. The basic reproductive number and its biological explanation are given. The stability conditions of the disease-free and endemic equilibria are obtained by analyzing its distribution of characteristic values. It is shown that the isolation ratio has an important influence on the basic reproductive number and the stability conditions. Taking the COVID-19 in Wuhan as an example, isolating more than 68% of the population can control the spread of the epidemic. This method can provide precise epidemic prevention strategies for government departments. Numerical simulations verify the effectiveness of the results.

Mathematical modeling of plus-strand RNA virus replication to identify broad-spectrum antiviral treatment strategies

Plus-strand RNA viruses are the largest group of viruses. Many are human pathogens that inflict a socio-economic burden. Interestingly, plus-strand RNA viruses share remarkable similarities in their replication. A hallmark of plus-strand RNA viruses is the remodeling of intracellular membranes to establish replication organelles (so-called "replication factories"), which provide a protected environment for the replicase complex, consisting of the viral genome and proteins necessary for viral RNA synthesis. In the current study, we investigate pan-viral similarities and virus-specific differences in the life cycle of this highly relevant group of viruses. We first measured the kinetics of viral RNA, viral protein, and infectious virus particle production of hepatitis C virus (HCV), dengue virus (DENV), and coxsackievirus B3 (CVB3) in the immuno-compromised Huh7 cell line and thus without perturbations by an intrinsic immune response. Based on these measurements, we developed a detailed mathematical model of the replication of HCV, DENV, and CVB3 and show that only small virus-specific changes in the model were necessary to describe the in vitro dynamics of the different viruses. Our model correctly predicted virus-specific mechanisms such as host cell translation shut off and different kinetics of replication organelles. Further, our model suggests that the ability to suppress or shut down host cell mRNA translation may be a key factor for in vitro replication efficiency which may determine acute self-limited or chronic infection. We further analyzed potential broad-spectrum antiviral treatment options in silico and found that targeting viral RNA translation, especially polyprotein cleavage, and viral RNA synthesis may be the most promising drug targets for all plus-strand RNA viruses. Moreover, we found that targeting only the formation of replicase complexes did not stop the viral replication in vitro early in infection, while inhibiting intracellular trafficking processes may even lead to amplified viral growth.

Author summary

Plus-strand RNA viruses comprise a large group of related and medically relevant viruses. The current global pandemic of COVID-19 caused by the SARS-coronavirus-2 as well as the constant spread of diseases such as dengue and chikungunya fever show the necessity of a comprehensive and precise analysis of plus-strand RNA virus infections. Plus-strand RNA viruses share similarities in their life cycle. To understand their within-host replication strategies, we developed a mathematical model that studies pan-viral similarities and virus-specific differences of three plus-strand RNA viruses, namely hepatitis C, dengue, and coxsackievirus. By fitting our model to in vitro data, we found that only small virus-specific variations in the model were required to describe the dynamics of all three viruses. Furthermore, our model predicted that ribosomes involved in viral RNA translation seem to be a key player in plus-strand RNA replication efficiency, which may determine acute or chronic infection outcome. Furthermore, our in-silico drug treatment analysis suggests that targeting viral proteases involved in polyprotein cleavage, in combination with viral RNA replication, may represent promising drug targets with broad-spectrum antiviral activity.

Proteomic Response of Aedes aegypti Larvae to Silver/Silver Chloride Nanoparticles Synthesized Using Bacillus thuringiensis subsp. israelensis Metabolites

Simple Summary

Aedes aegypti is a vector of important mosquito-borne diseases. Green synthesized nanoparticles (NPs) have been used to control the larvae of mosquitoes including A. aegypti. However, the molecular responses of A. aegypti larvae to green synthesized NPs remain unexplored. This work analyzed protein expression in A. aegypti larvae in response to treatment using green synthesized silver/silver chloride nanoparticles (Ag/AgCl NPs) based on two-dimensional polyacrylamide gel electrophoresis. Fifteen differentially expressed protein spots were selected for identification using mass spectrometry. The results showed that the six upregulated proteins in A. aegypti larvae responsible for green synthesized Ag/AgCl NP treatment were involved in mitochondrial dysfunction, DNA and protein damage, inhibition of cell proliferation, and cell apoptosis, implying the modes of actions of Ag/AgCl NPs. This finding has provided greater insight into the possible mechanisms of green synthesized Ag/AgCl NPs on the control of A. aegypti larvae.

Abstract

Silver/silver chloride nanoparticles (Ag/AgCl NPs) are an alternative approach to control the larvae of Aedes aegypti, a vector of mosquito-borne diseases. However, the molecular mechanisms of Ag/AgCl NPs to A. aegypti have not been reported. In this work, Ag/AgCl NPs were synthesized using supernatant, mixed toxins from Bacillus thuringiensis subsp. israelensis (Bti), and heterologously expressed Cry4Aa and Cry4Ba toxins. The images from scanning electron microscopy revealed that the Ag/AgCl NPs were spherical in shape with a size range of 25–100 nm. The larvicidal activity against A. aegypti larvae revealed that the Ag/AgCl NPs synthesized using the supernatant of Bti exhibited higher toxicity (LC₅₀ = 0.133 μg/mL) than the Ag/AgCl NPs synthesized using insecticidal proteins (LC₅₀ = 0.148–0.217 μg/mL). The proteomic response to Ag/AgCl NPs synthesized using the supernatant of Bti in A. aegypti larvae was compared to the ddH₂O-treated control. Two-dimensional gel electrophoresis analysis revealed 110 differentially expressed proteins, of which 15 were selected for identification using mass spectrometry. Six upregulated proteins (myosin I heavy chain, heat shock protein 70, the F₀F₁-type ATP synthase beta subunit, methyltransferase, protein kinase, and condensin complex subunit 3) that responded to Ag/AgCl NP treatment in A. aegypti were reported for NP treatments in different organisms. These results suggested that possible mechanisms of action of Ag/AgCl NPs on A. aegypti larvae are: mitochondrial dysfunction, DNA and protein damage, inhibition of cell proliferation, and cell apoptosis. The findings from this work provide greater insight into the action of green synthesized Ag/AgCl NPs on the control of A. aegypti larvae.

Spatial dynamics of dengue fever spreading for the coexistence of two serotypes with an application to the city of São Paulo, Brazil

BACKGROUND AND OBJECTIVE

Dengue fever is a disease in which individuals' spatial distribution and Aedes aegypti mosquitoes breeding places are important factors for the disease dynamics. Typically urban, dengue is a problem for least developed countries due to the ineffectiveness in controlling the vector and disorderly urbanization processes. The result is a composition of urban sanitation problems and areas with high demographic densities and intense flows of people. This paper explores the spatial distribution of vector breeding places to evaluate introducing a new dengue serotype to a population at equilibrium for a pre-existing serotype. The paper's objective is to analyze the spatial dynamics of dengue using variations of the basic reproduction number.

METHODS

A model based on probabilistic cellular automata is proposed to permitting the necessary flexibility to consider some spatial distributions of vector breeding places. Then, ordinary differential equations are used as a mean-field approach of the model, and the basic reproduction number (R₀) is derived considering the next-generation matrix method. A spatial approach for R₀ is also proposed, and the model is tested in a neighbourhood from the city of São Paulo, Brazil, to examine the potential risks of vector breeding cells distribution.

RESULTS

The results indicated that the more spread out these places, the higher are the values of R₀. When the model is applied to a neighbourhood in São Paulo, residential areas may boost the infections and must be under public vigilance to combat vector breeding sites.

CONCLUSIONS

Considering the mean-field approximation of the cellular automata model by ordinary differential equations, the basic reproduction number derived returned an estimative of the disease dynamics in the population. However, the spatial basic reproduction number was more assertive in showing areas with a higher disease incidence. Moreover, the model could be easily adapted to be used in real maps enabling simulations closer to real problems.

A transcriptomic atlas of Aedes aegypti reveals detailed functional organization of major body parts and gut regional specializations in sugar-fed and blood-fed adult females

Mosquitoes transmit numerous pathogens, but large gaps remain in our understanding of their physiology. To facilitate explorations of mosquito biology, we have created Aegypti-Atlas (http://aegyptiatlas.buchonlab.com/), an online resource hosting RNAseq profiles of Ae. aegypti body parts (head, thorax, abdomen, gut, Malpighian tubules, ovaries), gut regions (crop, proventriculus, anterior and posterior midgut, hindgut), and a gut time course of blood meal digestion. Using Aegypti-Atlas, we provide insights into regionalization of gut function, blood feeding response, and immune defenses. We find that the anterior and posterior midgut possess digestive specializations which are preserved in the blood-fed state. Blood feeding initiates the sequential induction and repression/depletion of multiple cohorts of peptidases. With respect to defense, immune signaling components, but not recognition or effector molecules, show enrichment in ovaries. Basal expression of antimicrobial peptides is dominated by holotricin and gambicin, which are expressed in carcass and digestive tissues, respectively, in a mutually exclusive manner. In the midgut, gambicin and other effectors are almost exclusively expressed in the anterior regions, while the posterior midgut exhibits hallmarks of immune tolerance. Finally, in a cross-species comparison between Ae. aegypti and Anopheles gambiae midguts, we observe that regional digestive and immune specializations are conserved, indicating that our dataset may be broadly relevant to multiple mosquito species. We demonstrate that the expression of orthologous genes is highly correlated, with the exception of a ‘species signature’ comprising a few highly/disparately expressed genes. With this work, we show the potential of Aegypti-Atlas to unlock a more complete understanding of mosquito biology.

Prediction of dengue fever outbreaks using climate variability and Markov chain Monte Carlo techniques in a stochastic susceptible-infected-removed model

The recent increase in the global incidence of dengue fever resulted in over 2.7 million cases in Latin America and many cases in Southeast Asia and has warranted the development and application of early warning systems (EWS) for futuristic outbreak prediction. EWS pertaining to dengue outbreaks is imperative; given the fact that dengue is linked to environmental factors owing to its dominance in the tropics. Prediction is an integral part of EWS, which is dependent on several factors, in particular, climate, geography, and environmental factors. In this study, we explore the role of increased susceptibility to a DENV serotype and climate variability in developing novel predictive models by analyzing RT-PCR and DENV-IgM confirmed cases in Singapore and Honduras, which reported high dengue incidence in 2019 and 2020, respectively. A random-sampling-based susceptible-infected-removed (SIR) model was used to obtain estimates of the susceptible fraction for modeling the dengue epidemic, in addition to the Bayesian Markov Chain Monte Carlo (MCMC) technique that was used to fit the model to Singapore and Honduras case report data from 2012 to 2020. Regression techniques were used to implement climate variability in two methods: a climate-based model, based on individual climate variables, and a seasonal model, based on trigonometrically varying transmission rates. The seasonal model accounted for 98.5% and 92.8% of the variance in case count in the 2020 Singapore and 2019 Honduras outbreaks, respectively. The climate model accounted for 75.3% and 68.3% of the variance in Singapore and Honduras outbreaks respectively, besides accounting for 75.4% of the variance in the major 2013 Singapore outbreak, 71.5% of the variance in the 2019 Singapore outbreak, and over 70% of the variance in 2015 and 2016 Honduras outbreaks. The seasonal model accounted for 14.2% and 83.1% of the variance in the 2013 and 2019 Singapore outbreaks, respectively, in addition to 91% and 59.5% of the variance in the 2015 and 2016 Honduras outbreaks, respectively. Autocorrelation lag tests showed that the climate model exhibited better prediction dynamics for Singapore outbreaks during the dry season from May to August and in the rainy season from June to October in Honduras. After incorporation of susceptible fractions, the seasonal model exhibited higher accuracy in predicting outbreaks of higher case magnitude, including those of the 2019–2020 dengue epidemic, in comparison to the climate model, which was more accurate in outbreaks of smaller magnitude. Such modeling studies could be further performed in various outbreaks, such as the ongoing COVID-19 pandemic to understand the outbreak dynamics and predict the occurrence of future outbreaks.

Estimating chikungunya virus transmission parameters and vector control effectiveness highlights key factors to mitigate arboviral disease outbreaks

Background

Viruses transmitted by Aedes mosquitoes have greatly expanded their geographic range in recent decades. They are considered emerging public health threats throughout the world, including Europe. Therefore, public health authorities must be prepared by quantifying the potential magnitude of virus transmission and the effectiveness of interventions.

Methodology

We developed a mathematical model with a vector-host structure for chikungunya virus transmission and estimated model parameters from epidemiological data of the two main autochthonous chikungunya virus transmission events that occurred in Southern France, in Montpellier (2014) and in Le Cannet-des-Maures (2017). We then performed simulations of the model using these estimates to forecast the magnitude of the foci of transmission as a function of the response delay and the moment of virus introduction.

Conclusions

The results of the different simulations underline the relative importance of each variable and can be useful to stakeholders when designing context-based intervention strategies. The findings emphasize the importance of, and advocate for early detection of imported cases and timely biological confirmation of autochthonous cases to ensure timely vector control measures, supporting the implementation and the maintenance of sustainable surveillance systems.

Dengue, chikungunya and Zika viruses have expanded their geographic range during recent decades and are now considered emerging threats in temperate areas. In particular, autochthonous transmissions of chikungunya virus (CHIKV) have regularly been observed in Europe since 2010. The increase in international travel and trade appear to be major factors, encouraging both a circulation of these viruses on a global scale and the dispersion of one of their main vectors, Aedes albopictus. This trend is likely to increase significantly in the future and improved preparedness and response strategies are essential to manage these emerging risks. In this respect of decision support, we developed a mathematical model for CHIKV transmission. We first estimated key model parameters of CHIKV transmission and vector control effectiveness, using data from the two main CHIKV transmission events which have already occurred in mainland France. The model was then used to forecast the magnitude of outbreaks as a function of the delay in implementing control measures, and from the moment of virus introduction during the mosquito vector season. This work will help provide stakeholders in public health with a greater understanding of the dynamics of CHIKV transmission, and with evidence for the implementation of sustainable surveillance systems.

Dengue virus infection modifies mosquito blood-feeding behavior to increase transmission to the host

Because dengue viruses are spread by mosquitoes during biting, transmission capacity depends on mosquito-biting behavior. For this reason, it is critical to understand how infection in mosquitoes influences biting. To answer this question, we deployed a multidisciplinary approach including high-resolution, multivariate biting behavior monitoring on mice, in vivo transmission assay, and mathematical modeling. We demonstrated that infected mosquitoes are more attracted to mice and bite more often to get the same amount of blood as uninfected mosquitoes. While the effect of increased attraction to host on transmission capacity is trivial, we showed that increased number of bites results in successive transmission. Eventually, we calculated that the infection-induced behavior changes tripled transmission capacity of mosquitoes.

Mosquito blood-feeding behavior is a key determinant of the epidemiology of dengue viruses (DENV), the most-prevalent mosquito-borne viruses. However, despite its importance, how DENV infection influences mosquito blood-feeding and, consequently, transmission remains unclear. Here, we developed a high-resolution, video-based assay to observe the blood-feeding behavior of Aedes aegypti mosquitoes on mice. We then applied multivariate analysis on the high-throughput, unbiased data generated from the assay to ordinate behavioral parameters into complex behaviors. We showed that DENV infection increases mosquito attraction to the host and hinders its biting efficiency, the latter resulting in the infected mosquitoes biting more to reach similar blood repletion as uninfected mosquitoes. To examine how increased biting influences DENV transmission to the host, we established an in vivo transmission model with immuno-competent mice and demonstrated that successive short probes result in multiple transmissions. Finally, to determine how DENV-induced alterations of host-seeking and biting behaviors influence dengue epidemiology, we integrated the behavioral data within a mathematical model. We calculated that the number of infected hosts per infected mosquito, as determined by the reproduction rate, tripled when mosquito behavior was influenced by DENV infection. Taken together, this multidisciplinary study details how DENV infection modulates mosquito blood-feeding behavior to increase vector capacity, proportionally aggravating DENV epidemiology. By elucidating the contribution of mosquito behavioral alterations on DENV transmission to the host, these results will inform epidemiological modeling to tailor improved interventions against dengue.

Impact of environmental factors on the spread of dengue fever in Sri Lanka

Dengue fever is a mosquito-borne viral disease caused by the dengue virus of the Flaviviridae family and is responsible for colossal health and economic burden worldwide. This study aimed to investigate the effect of environmental, seasonal, and spatial variations on the spread of dengue fever in Sri Lanka. The study used secondary data of monthly dengue infection and the monthly average of environmental parameters of 26 Sri Lankan regions from January 2015 to December 2019. Besides the descriptive measurements, Kendall's tau_b, Spearman's rho, and Kruskal-Wallis H test have been performed as bivariate analyses. The multivariate generalized linear negative binomial regression model was applied to determine the impacts of meteorological factors on dengue transmission. The aggregate negative binomial regression model disclosed that precipitation (odds ratio: 0.97, p < 0.05), humidity (odds ratio: 1.05, p < 0.01), and air pressure (odds ratio: 1.46, p < 0.01) were significantly influenced the spread of dengue fever in Sri Lanka. The bioclimatic zone is the vital factor that substantially affects the dengue infection, and the wet zone (odds ratio: 6.41, p < 0.05) was more at-risk than the dry zone. The climate season significantly influenced dengue fever transmission, and a higher infection rate was found (odds ratio: 1.46, p < 0.01) in the northeast monsoon season. The findings of this study facilitate policymakers to improve the existing dengue control strategies focusing on the meteorological condition in the local as well as global perspectives.

Climate change impacts on infectious diseases in the Eastern Mediterranean and the Middle East (EMME)-risks and recommendations

The Eastern Mediterranean and Middle East (EMME) region has rapid population growth, large differences in socio-economic levels between developed and developing countries, migration, increased water demand, and ecosystems degradation. The region is experiencing a significant warming trend with longer and warmer summers, increased frequency and severity of heat waves, and a drier climate. While climate change plays an important role in contributing to political instability in the region through displacement of people, food insecurity, and increased violence, it also increases the risks of vector-, water-, and food-borne diseases. Poorer and less educated people, young children and the elderly, migrants, and those with long-term health problems are at highest risk. A result of the inequalities among EMME countries is an inconsistency in the availability of reliable evidence about the impacts on infectious diseases. To help address this gap, a search of the literature was conducted as a basis for related recommended responses and suggested actions for preparedness and prevention. Since climate change already impacts the health of vulnerable populations in the EMME and will have a greater impact in future years, risk assessment and timely design and implementation of health preparedness and adaptation strategies are essential. Joint national and cross-border infectious diseases management systems for more effective preparedness and prevention are needed, supported by interventions that improve the environment. Without such cooperation and effective interventions, climate change will lead to an increasing morbidity and mortality in the EMME from infectious diseases, with a higher risk for the most vulnerable populations.

Climate change and infectious disease in Europe: Impact, projection and adaptation

Europeans are not only exposed to direct effects from climate change, but also vulnerable to indirect effects from infectious disease, many of which are climate sensitive, which is of concern because of their epidemic potential. Climatic conditions have facilitated vector-borne disease outbreaks like chikungunya, dengue, and West Nile fever and have contributed to a geographic range expansion of tick vectors that transmit Lyme disease and tick-borne encephalitis. Extreme precipitation events have caused waterborne outbreaks and longer summer seasons have contributed to increases in foodborne diseases. Under the Green Deal, The European Union aims to support climate change health policy, in order to be better prepared for the next health security threat, particularly in the aftermath of the traumatic COVID-19 experience. To bolster this policy process we discuss climate change-related hazards, exposures and vulnerabilities to infectious disease and describe observed impacts, projected risks, with policy entry points for adaptation to reduce these risks or avoid them altogether.

The epidemiology of Mayaro virus in the Americas: A systematic review and key parameter estimates for outbreak modelling

Mayaro virus (MAYV) is an arbovirus that is endemic to tropical forests in Central and South America, particularly within the Amazon basin. In recent years, concern has increased regarding MAYV's ability to invade urban areas and cause epidemics across the region. We conducted a systematic literature review to characterise the evolutionary history of MAYV, its transmission potential, and exposure patterns to the virus. We analysed data from the literature on MAYV infection to produce estimates of key epidemiological parameters, including the generation time and the basic reproduction number, R0. We also estimated the force-of-infection (FOI) in epidemic and endemic settings. Seventy-six publications met our inclusion criteria. Evidence of MAYV infection in humans, animals, or vectors was reported in 14 Latin American countries. Nine countries reported evidence of acute infection in humans confirmed by viral isolation or reverse transcription-PCR (RT-PCR). We identified at least five MAYV outbreaks. Seroprevalence from population based cross-sectional studies ranged from 21% to 72%. The estimated mean generation time of MAYV was 15.2 days (95% CrI: 11.7-19.8) with a standard deviation of 6.3 days (95% CrI: 4.2-9.5). The per-capita risk of MAYV infection (FOI) ranged between 0.01 and 0.05 per year. The mean R0 estimates ranged between 2.1 and 2.9 in the Amazon basin areas and between 1.1 and 1.3 in the regions outside of the Amazon basin. Although MAYV has been identified in urban vectors, there is not yet evidence of sustained urban transmission. MAYV's enzootic cycle could become established in forested areas within cities similar to yellow fever virus.

Global patterns of aegyptism without arbovirus

The world's most important mosquito vector of viruses, Aedes aegypti, is found around the world in tropical, subtropical and even some temperate locations. While climate change may limit populations of Ae. aegypti in some regions, increasing temperatures will likely expand its territory thus increasing risk of human exposure to arboviruses in places like Europe, Northern Australia and North America, among many others. Most studies of Ae. aegypti biology and virus transmission focus on locations with high endemicity or severe outbreaks of human amplified urban arboviruses, such as dengue, Zika, and chikungunya viruses, but rarely on areas at the margins of endemicity. The objective in this study is to explore previously published global patterns in the environmental suitability for Ae. aegypti and dengue virus to reveal deviations in the probability of the vector and human disease occurring. We developed a map showing one end of the gradient being higher suitability of Ae. aegypti with low suitability of dengue and the other end of the spectrum being equal and higher environmental suitability for both Ae. aegypti and dengue. The regions of the world with Ae. aegypti environmental suitability and no endemic dengue transmission exhibits a phenomenon we term 'aegyptism without arbovirus'. We then tested what environmental and socioeconomic variables influence this deviation map revealing a significant association with human population density, suggesting that locations with lower human population density were more likely to have a higher probability of aegyptism without arbovirus. Characterizing regions of the world with established populations of Ae. aegypti but little to no autochthonous transmission of human-amplified arboviruses is an important step in understanding and achieving aegyptism without arbovirus.

Lessons from a Surgical Center Satellite Warehouse in a Large Brazilian Public Hospital

Brazilian public hospitals face several operational problems not only related to poor public management practices and their complex nature, but also the economic, and social contexts. Considering this scenario and the fact that efforts in supply management might affect a hospital organization’s excellence, this research aims to identify improvements in the logistic operations at the surgical center satellite warehouse of a Public Hospital located in Brazil. A case study based on an exploratory and qualitative approach was conducted by employing document analysis, semi-structured interviews, and on-site observations. Seven major problems concerning lack of surgical material, the non-definition of crucial logistic parameters, low information flow, surgical supply control, and management problems were pointed and addressed by seven independent but complementary actions that considered the Brazilian healthcare system’s particularities. Given the nature of exploratory research, the results are not exhaustive and cannot be generalized to different contexts. However, they help understand that reducing the waste of the logistics processes makes it possible to improve the attention to the local population that uses public health services.

Asynchronicity of endemic and emerging mosquito-borne disease outbreaks in the Dominican Republic

Mosquito-borne viruses threaten the Caribbean due to the region's tropical climate and seasonal reception of international tourists. Outbreaks of chikungunya and Zika have demonstrated the rapidity with which these viruses can spread. Concurrently, dengue fever cases have climbed over the past decade. Sustainable disease control measures are urgently needed to quell virus transmission and prevent future outbreaks. Here, to improve upon current control methods, we analyze temporal and spatial patterns of chikungunya, Zika, and dengue outbreaks reported in the Dominican Republic between 2012 and 2018. The viruses that cause these outbreaks are transmitted by Aedes mosquitoes, which are sensitive to seasonal climatological variability. We evaluate whether climate and the spatio-temporal dynamics of dengue outbreaks could explain patterns of emerging disease outbreaks. We find that emerging disease outbreaks were robust to the climatological and spatio-temporal constraints defining seasonal dengue outbreak dynamics, indicating that constant surveillance is required to prevent future health crises.

Survey on neutralizing antibodies against Zika virus eighteen months post-outbreak in two southern Thailand communities

Background

In 2016 and 2017, Zika virus (ZIKV) infection outbreaks occurred in two communities in southern Thailand. This re-immerging infection can widely spread by mosquito bites and cause serious complications in a central nervous system among children born to infected mothers. Thus, they should be protected. This study aims to (1) To determine the prevalence of neutralizing ZIKV antibodies in the post-outbreak areas among the general population and pregnancy women residing at various distances from the houses of the nearest index patients; (2) To examine the cross-neutralizing capacity of antibodies against ZIKV on other flaviviruses commonly found in the study areas; (3) To identify factors associated with the presence of neutralizing ZIKV antibodies.

Methods

The two post-outbreak communities were visited at 18 months after the outbreaks. We enrolled (1) 18 confirmed ZIKV infected (index) cases, (2) sample of 554 neighbors in the outbreak areas who lived at various distances from the index patients’ houses, (3) 190 residents of non-outbreak areas, and (4) all pregnant women regardless of gestational age residing in the study areas (n = 805). All serum specimens underwent the plaque reduction neutralization test (PRNT). Ten randomly selected ZIKV seropositive and ten randomly selected seronegative specimens were tested for dengue virus serotypes 1–4 (DENV1–4) and Japanese encephalitis virus (JEV) antibodies using PRNT90. Serum titer above 1:10 was considered positive. Multiple logistic regression was used to assess factors associated with seropositivity.

Results

Out of all 18 index cases, 9 remained seropositive. The seroprevalence (95% CI) in the two outbreak areas were 43.7% (35.9–51.6%) and 29.7% (23.3–36.0%) in general population, and 24.3% (20.1–28.8%) and 12.8% (9.7–16.5%) in pregnant women. Multivariate analysis showed that seropositivity was independent of the distance gradient from the index’s houses. However, being elderly was associated with seropositivity. DENV1–4 and JEV neutralizing antibodies were present in most ZIKV-positive and negative subsamples.

Conclusion

Protective herd immunity for ZIKV infection is inadequate, especially among pregnant women in the two post-outbreak areas in southern Thailand.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-020-05654-8.

Identification of Aedes (Diptera: Culicidae) Species and Arboviruses Circulating in Arauca, Eastern Colombia

The identification of vector species and their natural infection with arboviruses results in important data for the control of their transmission. However, for the eastern region of Colombia, this information is limited. Therefore, this study morphologically and molecularly identified species of the genus Aedes and the detection of arboviruses (Dengue, Chikungunya, Zika, and Mayaro) in female mosquitoes (individually) present in three municipalities (Saravena, Arauquita, and Tame) by amplifying the genetic material using RT-PCR (reverse transcriptase polymerase chain reaction) in the department of Arauca, eastern Colombia. Inconsistencies between morphological and molecular identification were detected in 13 individuals with Aedes albopictus initially determined as Aedes aegypti based on morphology (n = 13). Molecular identification showed the simultaneous presence of A. aegypti (n = 111) and A. albopictus (n = 58) in the urban municipalities of Saravena and Arauquita. These individuals were naturally infected with Dengue virus type 1 (DENV-1) and Chikungunya virus (CHIKV). The most frequent arbovirus was DENV-1 with an infection rate of 40.7% (11/27) for A. aegypti and 39.7% (23/58) for A. albopictus, which was followed by CHIKV with an infection rate of 1.8% for A. aegypti (2/111) and 6.9% for A. albopictus (4/58). Additionally, a mixed infection of DENV-1 and CHIKV was obtained in 4.5% of A. aegypti (5/111). Zika virus (ZIKV) and Mayaro virus (MAYV) infections were not detected. This study found that barcoding (fragment gene COI) is a successful method for identifying Aedes species. Additionally, we recommend the individual processing of insects as a more accurate strategy for arboviruses detection since the infection rate is obtained and co-infection between DENV-1 and CHIKV is also possible.

The effects of regional climatic condition on the spread of COVID-19 at global scale

The pandemic outbreak of the novel coronavirus epidemic disease (COVID-19) is spreading like a diffusion-reaction in the world and almost 208 countries and territories are being affected around the globe. It became a sever health and socio-economic problem, while the world has no vaccine to combat this virus. This research aims to analyze the connection between the fast spread of COVID-19 and regional climate parameters over a global scale. In this research, we collected the data of COVID-19 cases from the time of 1st reported case to the 5th June 2020 in different affected countries and regional climatic parameters data from January 2020 to 5th June 2020. It was found that most of the countries located in the relatively lower temperature region show a rapid increase in the COVID-19 cases than the countries locating in the warmer climatic regions despite their better socio-economic conditions. A correlation between metrological parameters and COVID-19 cases was observed. Average daylight hours are correlated to total the COVID-19 cases with a coefficient of determination of 0.42, while average high-temperature shows a correlation of 0.59 and 0.42 with total COVID-19 cases and death cases respectively. The finding of the study will help international health organizations and local administrations to combat and well manage the spread of COVID-19.

Investigation of the ability of the oviposition-stimulant lectin from Moringa oleifera seeds (WSMoL) to bind with membrane proteins present in the legs of Aedes aegypti

The mosquito Aedes aegypti L. is a vector transmitting diseases such as dengue, chikungunya and Zika virus fever. The water-soluble lectin from Moringa oleifera Lam. seeds (WSMoL) is larvicidal, ovicidal and can stimulate oviposition in A. aegypti. This study aimed to investigate whether WSMoL could bind to membrane proteins from A. aegypti legs. Initially, proteins from the legs were extracted using sodium deoxycholate, digitonin, dodecyl sodium sulfate (SDS) or Triton X-100. The protein concentration was found to be higher in the extract obtained using Triton X-100, which was applied to a WSMoL-Sepharose column. The adsorbed proteins were evaluated using gel filtration chromatography and polyacrylamide gel electrophoresis (PAGE) in presence of SDS. The similarity in the sequences of adsorbed proteins with those available in databases was determined. The proteins adsorbed on the matrix were eluted forming a single peak. Gel filtration chromatography and SDS-PAGE revealed the presence of proteins with molecular masses of approximately 20 kDa and polypeptide bands of 17.0 and 23.7 kDa, respectively. MS/MS analysis indicated similarity between these proteins and ABC carriers, which are expressed in the legs of mosquitos. WSMoL could bind to membrane proteins in the legs of A. aegypti females and induce oviposition through these interactions.