Temperature impacts on dengue emergence in the United States: Investigating the role of seasonality and climate change

Estimating dynamics of dengue disease in Colombo district of Sri Lanka with environmental impact by quantifying the per-capita vector density

Dengue is a vector-borne disease transmitted to humans by vectors of genus Aedes causing a global threat to health, social, and economic sectors in many of the tropical countries including Sri Lanka. In Sri Lanka, the tropical climate, marked by seasonal weather primarily influenced by monsoons, fosters optimal conditions for the virus to spread efficiently. This heightened transmission results in increased per-capita vector density. In this work, we investigate the dynamic influence of environmental conditions on dengue emergence in Colombo district - the geographical region with the highest recorded dengue threat in Sri Lanka. An iterative approach is employed to dynamically estimate dengue cases leveraging the Markov chain Monte Carlo simulations, utilizing the dynamics of four seasons per year influenced by monsoon weather patterns governing in the region. The developed algorithm allows to estimate the risk of dengue outbreaks in 2017 and 2019 with high precision, facilitating accurate forecasts of upcoming disease emergence patterns for better preparedness. The uncertainty quantification not only validated the accuracy of outbreak estimates but also showcased the model's capacity to capture extreme cases and revealed undisclosed external factors such as human mobility and environmental pollution that might affect dengue transmission in the Colombo district of Sri Lanka.

Temperature and humidity as drivers for the transmission of zoonotic diseases

Zoonotic diseases remain a persistent threat to global public health. Many major zoonotic pathogens exhibit seasonal patterns associated with climatic variations. Quantifying the impacts of environmental variables such as temperature and humidity on disease transmission dynamics is critical for improving prediction and control measures. This review synthesizes current evidence on the relationships between temperature and humidity and major zoonotic diseases, including malaria, dengue, rabies, anisakiasis, and influenza. Overall, this review highlighted some overarching themes across the different zoonotic diseases examined. Higher temperatures within suitable ranges were generally associated with increased transmission risks, while excessively high or low temperatures had adverse effects. Humidity exhibited complex nonlinear relationships, facilitating transmission in certain temperature zones but inhibiting it in others. Heavy rainfall and high humidity were linked to vector‐borne disease outbreaks such as malaria by enabling vector breeding. However, reduced incidence of some diseases like dengue fever was observed with high rainfall. To address existing knowledge gaps, future research efforts should prioritize several key areas: enhancing data quality through robust surveillance and the integration of high‐resolution microclimate data; standardizing analytical frameworks and leveraging advanced methodologies such as machine learning; conducting mechanistic studies to elucidate pathogen, vector, and host responses to climatic stimuli; adopting interdisciplinary approaches to account for interacting drivers; and projecting disease impacts under various climate change scenarios to inform adaptation strategies. Investing in these research priorities can propel the development of evidence‐based climate‐aware disease prediction and control measures, ultimately safeguarding public health more effectively.

The influence of the larval microbiome on susceptibility to Zika virus is mosquito genotype-dependent

The microbiome of the mosquito Aedes aegypti is largely determined by the environment and influences mosquito susceptibility for arthropod-borne viruses (arboviruses). Larval interactions with different bacteria can have carry-over effects on adult Ae. aegypti replication of arboviruses, but little is known about the role that mosquito host genetics play in determining how larval-bacterial interactions shape Ae aegypti susceptibility to arboviruses. To address this question, we isolated single bacterial isolates and complex microbiomes from Ae. aegypti larvae from various field sites in Senegal. Either single bacterial isolates or complex microbiomes were added to two different genetic backgrounds of Ae. aegypti in a gnotobiotic larval system. Using 16S amplicon sequencing we showed that the bacterial community structure differs between the two genotypes of Ae. aegypti when given identical microbiomes, and the abundance of single bacterial taxa differed between Ae. aegypti genotypes. Using single bacterial isolates or the entire preserved complex microbiome, we tested the ability of specific larval microbiomes to drive differences in infection rates for Zika virus in different genetic backgrounds of Ae. aegypti. We observed that the proportion of Zika virus-infected adults was dependent on the interaction between the larval microbiome and Ae. aegypti host genetics. By using the larval microbiome as a component of the environment, these results demonstrate that interactions between the Ae. aegypti genotype and its environment can influence Zika virus infection. As Ae. aegypti expands and adapts to new environments under climate change, an understanding of how different genotypes interact with the same environment will be crucial for implementing arbovirus transmission control strategies.

Convergent trends and spatiotemporal patterns of Aedes-borne arboviruses in Mexico and Central America

BACKGROUND

Aedes-borne arboviruses cause both seasonal epidemics and emerging outbreaks with a significant impact on global health. These viruses share mosquito vector species, often infecting the same host population within overlapping geographic regions. Thus, comparative analyses of the virus evolutionary and epidemiological dynamics across spatial and temporal scales could reveal convergent trends.

METHODOLOGY/PRINCIPAL FINDINGS

Focusing on Mexico as a case study, we generated novel chikungunya and dengue (CHIKV, DENV-1 and DENV-2) virus genomes from an epidemiological surveillance-derived historical sample collection, and analysed them together with longitudinally-collected genome and epidemiological data from the Americas. Aedes-borne arboviruses endemically circulating within the country were found to be introduced multiple times from lineages predominantly sampled from the Caribbean and Central America. For CHIKV, at least thirteen introductions were inferred over a year, with six of these leading to persistent transmission chains. For both DENV-1 and DENV-2, at least seven introductions were inferred over a decade.

CONCLUSIONS/SIGNIFICANCE

Our results suggest that CHIKV, DENV-1 and DENV-2 in Mexico share evolutionary and epidemiological trajectories. The southwest region of the country was determined to be the most likely location for viral introductions from abroad, with a subsequent spread into the Pacific coast towards the north of Mexico. Virus diffusion patterns observed across the country are likely driven by multiple factors, including mobility linked to human migration from Central towards North America. Considering Mexico's geographic positioning displaying a high human mobility across borders, our results prompt the need to better understand the role of anthropogenic factors in the transmission dynamics of Aedes-borne arboviruses, particularly linked to land-based human migration.

Role of air pollutants in dengue fever incidence: evidence from two southern cities in Taiwan

Air pollution may be involved in spreading dengue fever (DF) besides rainfalls and warmer temperatures. While particulate matter (PM), especially those with diameter of 10 μm (PM10) or 2.5 μm or less (PM25), and NO2 increase the risk of coronavirus 2 infection, their roles in triggering DF remain unclear. We explored if air pollution factors predict DF incidence in addition to the classic climate factors. Public databases and DF records of two southern cities in Taiwan were used in regression analyses. Month order, PM10 minimum, PM2.5 minimum, and precipitation days were retained in the enter mode model, and SO2 minimum, O3 maximum, and CO minimum were retained in the stepwise forward mode model in addition to month order, PM10 minimum, PM2.5 minimum, and precipitation days. While PM2.5 minimum showed a negative contribution to the monthly DF incidence, other variables showed the opposite effects. The sustain of month order, PM10 minimum, PM2.5 minimum, and precipitation days in both regression models confirms the role of classic climate factors and illustrates a potential biological role of the air pollutants in the life cycle of mosquito vectors and dengue virus and possibly human immune status. Future DF prevention should concern the contribution of air pollution besides the classic climate factors.

The influence of the larval microbiome on susceptibility to Zika virus is mosquito genotype dependent

The microbiome of the mosquito Aedes aegypti is largely determined by the environment and influences mosquito susceptibility for arthropod-borne viruses (arboviruses). Larval interactions with different bacteria can influence adult Ae. aegypti replication of arboviruses, but little is known about the role that mosquito host genetics play in determining how larval-bacterial interactions shape Ae aegypti susceptibility to arboviruses. To address this question, we isolated single bacterial isolates and complex microbiomes from Ae. aegypti larvae from various field sites in Senegal. Either single bacterial isolates or complex microbiomes were added to two different genetic backgrounds of Ae. aegypti in a gnotobiotic larval system. Using 16S amplicon sequencing we show that similarities in bacterial community structures when given identical microbiomes between different genetic backgrounds of Ae. aegypti was dependent on the source microbiome, and the abundance of single bacterial taxa differed between Ae. aegypti genotypes. Using single bacterial isolates or the entire preserved complex microbiome, we tested the ability of specific microbiomes to drive differences in infection rates for Zika virus in different genetic backgrounds of Ae. aegypti . We observed that the proportion of Zika virus-infected adults was dependent on the interaction between the larval microbiome and Ae. aegypti host genetics. By using the larval microbiome as a component of the environment, these results demonstrate that interactions between the Ae. aegypti genotype and its environment can influence Zika virus infection. As Ae. aegypti expands and adapts to new environments under climate change, an understanding of how different genotypes interact with the same environment will be crucial for implementing arbovirus transmission control strategies.

The relative importance of key meteorological factors affecting numbers of mosquito vectors of dengue fever

Although single factors such as rainfall are known to affect the population dynamics of Aedes albopictus, the main vector of dengue fever in Eurasia, the synergistic effects of different meteorological factors are not fully understood. To address this topic, we used meteorological data and mosquito-vector association data including Breteau and ovitrap indices in key areas of dengue outbreaks in Guangdong Province, China, to formulate a five-stage mathematical model for Aedes albopictus population dynamics by integrating multiple meteorological factors. Unknown parameters were estimated using a genetic algorithm, and the results were analyzed by k-Shape clustering, random forest and grey correlation analysis. In addition, the population density of mosquitoes in 2022 was predicted and used for evaluating the effectiveness of the model. We found that there is spatiotemporal heterogeneity in the effects of temperature and rainfall and their distribution characteristics on the diapause period, the numbers of peaks in mosquito densities in summer and the annual total numbers of adult mosquitoes. Moreover, we identified the key meteorological indicators of the mosquito quantity at each stage and that rainfall (seasonal rainfall and annual total rainfall) was more important than the temperature distribution (seasonal average temperature and temperature index) and the uniformity of rainfall annual distribution (coefficient of variation) for most of the areas studied. The peak rainfall during the summer is the best indicator of mosquito population development. The results provide important theoretical support for the future design of mosquito vector control strategies and early warnings of mosquito-borne diseases.

Climate change and the displaced person: how vectors and climate are changing the landscape of infectious diseases among displaced and migrant populations

BACKGROUND

As the climate crisis grows, so does the global burden of displacement. Displacement, whether a direct or indirect consequence of natural disaster, can lead to dire health sequelae. Skin health is no exception to this, with dermatologic disease being a leading concern reported by those who care for displaced persons. Health professionals who provide dermatologic care for displaced persons benefit from understanding how climate change impacts the global profile of infectious agents.

METHODS

This review was performed using PubMed and Google Scholar. Search terms included climate change, displaced person, internally displaced person, and refugee, as well as searches of infectious disease dermatology and the specific diseases of interest. Case reports, case series, reviews, and original research articles were included in this review. Non-English studies were not included.

RESULTS

In this manuscript several key infectious agents were identified, and we discuss the skin manifestations and impact of climate change on cutaneous leishmaniasis, dengue, chikungunya, zika, malaria, pediculosis, cutaneous larva migrans, cholera, and varicella zoster.

CONCLUSIONS

Climate change plays a significant role in the challenges faced by displaced persons, including their skin health. Among the many consequences of climate change is its altering of the ecological profile of infectious agents and vectors that impact displaced persons. Being familiar with this impact can improve dermatologic care for this vulnerable population.

Beyond the Unknown: A Broad Framing for Preparedness for Emerging Infectious Threats

There have been multiple instances of novel pathogen emergence that have affected the health and security of the global community. To highlight that these novel pathogens presented a clear danger to public health, the WHO included "Disease X" on their list of priority pathogens in 2018. Indeed, since the emergence of SARS-CoV-2, Disease X has been pointed to as the looming threat of "the next big thing." However, developing surveillance and preparedness plans with Disease X as the linchpin is too narrow and ignores a large swath of potential threats from already identified, often neglected diseases. We propose instead the idea of "Disease f(x)" as a preferred call to arms with which to prioritize research and programmatic development. The common mathematical notation f(x) represents the knowledge that outbreaks are a function of many variables that define the transmission trajectory of that pathogen. Disease f(x) exploits commonalities across pathogen groupings while recognizing that emergences and outbreaks are fluid and that responses need to be agile and progressively tailored to specific pathogens with cultural and regional context. Adoption of this mindset across sectors, including biotechnology, disaster management, and epidemiology, will allow us to develop more efficient and effective responses to address the next major infectious threat.

How do i bite thee? let me count the ways: Exploring the implications of individual biting habits of Aedes aegypti for dengue transmission

In models of mosquito-borne transmission, the mosquito biting rate is an influential parameter, and understanding the heterogeneity of the process of biting is important, as biting is usually assumed to be relatively homogeneous across individuals, with time-between-bites described by an exponentially distributed process. However, these assumptions have not been addressed through laboratory experimentation. We experimentally investigated the daily biting habits of Ae. aegypti at three temperatures (24°C, 28°C, and 32°C) and determined that there was individual heterogeneity in biting habits (number of bites, timing of bites, etc.). We further explored the consequences of biting heterogeneity using an individual-based model designed to examine whether a particular biting profile determines whether a mosquito is more or less likely to 1) become exposed given a single index case of dengue (DENV) and 2) transmit to a susceptible human individual. Our experimental results indicate that there is heterogeneity among individuals and among temperature treatments. We further show that this results in altered probabilities of transmission of DENV to and from individual mosquitoes based on biting profiles. While current model representation of biting may work under some conditions, it might not uniformly be the best fit for this process. Our data also confirm that biting is a non-monotonic process with temperatures around 28°C being optimum.

An ensemble forecast system for tracking dynamics of dengue outbreaks and its validation in China

As a common vector-borne disease, dengue fever remains challenging to predict due to large variations in epidemic size across seasons driven by a number of factors including population susceptibility, mosquito density, meteorological conditions, geographical factors, and human mobility. An ensemble forecast system for dengue fever is first proposed that addresses the difficulty of predicting outbreaks with drastically different scales. The ensemble forecast system based on a susceptible-infected-recovered (SIR) type of compartmental model coupled with a data assimilation method called the ensemble adjusted Kalman filter (EAKF) is constructed to generate real-time forecasts of dengue fever spread dynamics. The model was informed by meteorological and mosquito density information to depict the transmission of dengue virus among human and mosquito populations, and generate predictions. To account for the dramatic variations of outbreak size in different seasons, the effective population size parameter that is sequentially updated to adjust the predicted outbreak scale is introduced into the model. Before optimizing the transmission model, we update the effective population size using the most recent observations and historical records so that the predicted outbreak size is dynamically adjusted. In the retrospective forecast of dengue outbreaks in Guangzhou, China during the 2011-2017 seasons, the proposed forecast model generates accurate projections of peak timing, peak intensity, and total incidence, outperforming a generalized additive model approach. The ensemble forecast system can be operated in real-time and inform control planning to reduce the burden of dengue fever.

Effects of Guangzhou seasonal climate change on the development of Aedes albopictus and its susceptibility to DENV-2

The susceptibility of Asian tiger mosquitoes to DENV-2 in different seasons was observed in simulated field environments as a reference to design dengue fever control strategies in Guangzhou. The life table experiments of mosquitoes in four seasons were carried out in the field. The susceptibility of Ae. albopictus to dengue virus was observed in both environments in Guangzhou in summer and winter. Ae. albopictus was infected with dengue virus by oral feeding. On day 7 and 14 after infection, the viral load in the head, ovary, and midgut of the mosquito was detected using real-time fluorescent quantitative PCR. Immune-associated gene expression in infected mosquitoes was performed using quantitative real-time reverse transcriptase PCR. The hatching rate and pupation rate of Ae. albopictus larvae in different seasons differed significantly. The winter hatching rate of larvae was lower than that in summer, and the incubation time was longer than in summer. In the winter field environment, Ae. albopictus still underwent basic growth and development processes. Mosquitoes in the simulated field environment were more susceptible to DENV-2 than those in the simulated laboratory environment. In the midgut, viral RNA levels on day 7 in summer were higher than those on day 7 in winter (F = 14.459, P = 0.01); ovarian viral RNA levels on day 7 in summer were higher than those on day 7 in winter (F = 8.656, P < 0.001), but there was no significant difference in the viral load at other time points (P > 0.05). Dicer-2 mRNA expression on day 7 in winter was 4.071 times than that on day 7 in summer: the viral load and Dicer-2 expression correlated moderately. Ae. albopictus could still develop and transmit dengue virus in winter in Guangzhou. Mosquitoes under simulated field conditions were more susceptible to DENV-2 than those under simulated laboratory conditions.

Game-Theoretical Model of the Voluntary Use of Insect Repellents to Prevent Zika Fever

Zika fever is an emerging mosquito-borne disease. While it often causes no or only mild symptoms that are similar to dengue fever, Zika virus can spread from a pregnant woman to her baby and cause severe birth defects. There is no specific treatment or vaccine, but the disease can be mitigated by using several control strategies, generally focusing on the reduction in mosquitoes or mosquito bites. In this paper, we model Zika virus transmission and incorporate a game-theoretical approach to study a repeated population game of DEET usage to prevent insect bites. We show that the optimal use effectively leads to disease elimination. This result is robust and not significantly dependent on the cost of the insect repellents.

CO2 biocapture by Scenedesmus sp. grown in industrial wastewater

Greenhouse gases (GHG) emissions are widely related to climate change, triggering several environmental problems of global concern and producing environmental, social, and economic negative impacts. Therefore, global research seeks to mitigate greenhouse gas emissions. On the other hand, the use of wastes under a circular economy scheme generates subproducts from the range of high to medium-value, representing a way to help sustainable development. Therefore, the use of wastewater as a culture medium to grow microalgae strains that biocapture environmental CO₂, is a proposal with high potential to reduce the GHG presence in the environment. In this work, Scenedesmus sp. was cultivated using BG-11 medium and industrial wastewater (IWW) as a culture medium with three different CO₂ concentrations, 0.03%, 10%, and 20% to determine their CO₂ biocapture potential. Furthermore, the concomitant removal of COD, nitrates, and total phosphorus in wastewater was evaluated. Scenedesmus sp. achieves a biomass concentration of 1.9 g L^-1 when is grown in BG-11 medium, 0.69 g L^-1 when is grown in a combination of BG-11 medium and 25% of industrial wastewater; both cases with 20% CO₂ supplied. The maximum CO₂ removal efficiency (8.4%, 446 ± 150 mg CO₂ L^-1 day^-1) was obtained with 10% CO₂ supplied and using a combination of BG-11 medium and 50% IWW (T2). Also, the highest removal of COD was reached with a combination of BG-11 medium and T2 with a supply of 20% CO₂ (82% of COD removal). Besides, the highest nitrates removal was achieved with a combination of BG-11 medium and 75% IWW (T3) with a supply of 10% CO₂ (42% of nitrates removal) and the maximum TP removal was performed with the combination of BG-11 medium and 25% IWW (T1) with a supply of 10% CO₂ (67% of TP removal). These results indicate that industrial wastewater can be used as a culture media for microalgae growth and CO₂ biocapture can be performed as concomitant processes.

A Temperature Conditioned Markov Chain Model for Predicting the Dynamics of Mosquito Vectors of Disease

Understanding and predicting mosquito population dynamics is crucial for gaining insight into the abundance of arthropod disease vectors and for the design of effective vector control strategies. In this work, a climate-conditioned Markov chain (CMC) model was developed and applied for the first time to predict the dynamics of vectors of important medical diseases. Temporal changes in mosquito population profiles were generated to simulate the probabilities of a high population impact. The simulated transition probabilities of the mosquito populations achieved from the trained model are very near to the observed data transitions that have been used to parameterize and validate the model. Thus, the CMC model satisfactorily describes the temporal evolution of the mosquito population process. In general, our numerical results, when temperature is considered as the driver of change, indicate that it is more likely for the population system to move into a state of high population level when the former is a state of a lower population level than the opposite. Field data on frequencies of successive mosquito population levels, which were not used for the data inferred MC modeling, were assembled to obtain an empirical intensity transition matrix and the frequencies observed. Our findings match to a certain degree the empirical results in which the probabilities follow analogous patterns while no significant differences were observed between the transition matrices of the CMC model and the validation data (ChiSq = 14.58013, df = 24, p = 0.9324451). The proposed modeling approach is a valuable eco-epidemiological study. Moreover, compared to traditional Markov chains, the benefit of the current CMC model is that it takes into account the stochastic conditional properties of ecological-related climate variables. The current modeling approach could save costs and time in establishing vector eradication programs and mosquito surveillance programs.

The impact of climate change on neglected tropical diseases: a systematic review

Neglected tropical diseases (NTDs) are a diverse group of diseases that continue to affect >1 billion people, with these diseases disproportionately impacting vulnerable populations and territories. Climate change is having an increasing impact on public health in tropical and subtropical areas and across the world and can affect disease distribution and transmission in potentially diverse ways. Improving our understanding of how climate change influences NTDs can help identify populations at risk to include in future public health interventions. Articles were identified by searching electronic databases for reports of climate change and NTDs between 1 January 2010 and 1 March 2020. Climate change may influence the emergence and re-emergence of multiple NTDs, particularly those that involve a vector or intermediate host for transmission. Although specific predictions are conflicting depending on the geographic area, the type of NTD and associated vectors and hosts, it is anticipated that multiple NTDs will have changes in their transmission period and geographic range and will likely encroach on regions and populations that have been previously unaffected. There is a need for improved surveillance and monitoring to identify areas of NTD incursion and emergence and include these in future public health interventions.

A Bibliometric Analysis on Dengue Outbreaks in Tropical and Sub-Tropical Climates Worldwide Since 1950

Severe dengue outbreaks (DOs) affect the majority of Asian and Latin American countries. Whether all DOs always occurred in sub-tropical and tropical areas (STTA) has not been verified. We downloaded abstracts by searching keywords “dengue (MeSH Major Topic)” from Pubmed Central since 1950, including three collections: country names in abstracts (CNA), no abstracts (WA), and no country names in abstracts (Non-CNA). Visualizations were created to present the DOs across countries/areas in STTA. The percentages of mentioned country names and authors’ countries in STTA were computed on the CNA and Non-CNA bases. The social network analysis was applied to highlight the most cited articles and countries. We found that (1) three collections are 3427 (25.48%), 3137 (23.33%), and 6884 (51.19%) in CNA, WA, and Non-CNA, respectively; (2) the percentages of 94.3% and 79.9% were found in the CNA and Non-CNA groups; (3) the most mentioned country in abstracts were India, Thailand, and Brazil; (4) most authors in the Non-CNA collections were from the United States, Brazil, and China; (5) the most cited article (PMID = 23563266) authored by Bhatt et al. had 2604 citations since 2013. Our findings provide in-depth insights into the DO knowledge. The research approaches are recommended for authors in research on other infectious diseases in the future, not just limited to the DO topic.

Susceptible host availability modulates climate effects on dengue dynamics

Experiments and models suggest that climate affects mosquito-borne disease transmission. However, disease transmission involves complex nonlinear interactions between climate and population dynamics, which makes detecting climate drivers at the population level challenging. By analysing incidence data, estimated susceptible population size, and climate data with methods based on nonlinear time series analysis (collectively referred to as empirical dynamic modelling), we identified drivers and their interactive effects on dengue dynamics in San Juan, Puerto Rico. Climatic forcing arose only when susceptible availability was high: temperature and rainfall had net positive and negative effects respectively. By capturing mechanistic, nonlinear and context-dependent effects of population susceptibility, temperature and rainfall on dengue transmission empirically, our model improves forecast skill over recent, state-of-the-art models for dengue incidence. Together, these results provide empirical evidence that the interdependence of host population susceptibility and climate drives dengue dynamics in a nonlinear and complex, yet predictable way.

Coagulation-flocculation: a potential application for mosquito Larval Source Management (LSM)

Larval mosquitoes have a more limited home range and lower resistance to adverse environment than adults, thus can be ideal targets for vector control in some cases. Coagulation-flocculation technology, which could be used for water treatment in breeding sites of several vector mosquito species, can significantly change both the distribution of organic particles and surface sediment characteristics in water environment. The aim of this study was to explore the effect, principle and possibility of using coagulation-flocculation technology in immature mosquitoes killing. In this study, dechlorinated water was treated with Poly Aluminum Chloride (PACl, sewage treatment using), and we observed the impacts of PACl treatment on the development and survival of immature Culex pipiens pallens mosquitoes. When exposed to PACl treatment, physical effect is believed to be a main reason of coagulation-flocculation caused high larvae mortality: Ⅰ) alum floc layer increases the difficulty of larvae foraging, leads larvae starving to death; (Ⅱ) the little floc particles could attach to the lateral hair of larvae, which impede floatation process and then surface respiration by larval mosquitoes. The alum floc layer had a good killing effect on the mosquito larvae, presented the half lethal time (LT₅₀) of 2d, the 90% lethal time (LT₉₀) of 8.7±7.3 ∼ 14±4.5 d, and the pupation rate of 0 ∼ (6.5±0.5)%, respectively. Our results indicates alum floc, produced by PACl coagulation-flocculation, was shown to be highly active against 1^st∼2^nd instar larvae, the high mortality rate of immature mosquitoes as a result of physical effect. The observations suggest that coagulation-flocculation technology offers a novel potential approach to a sustainable and low-impact mosquito control method.

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.

Climate Change and Inpatient Dermatology

PURPOSE OF REVIEW

Climate change represents a major existential threat facing the global community, and it has already begun to affect human health in a multitude of ways. This review highlights and discusses the implications that climate change has already had and is expected to have for inpatient dermatologists.

RECENT FINDINGS

There are a variety of conditions affected by climate changes. The distribution and frequencies of infectious diseases and their vectors are changing in line with variations in climate conditions. Increased temperatures have already been associated with exacerbation of existing skin conditions, such as atopic dermatitis, and recent evidence suggests that higher temperatures will also magnify the effects of harmful ultraviolet radiation. Extreme weather events that result from climate change are followed by an array of dermatologic conditions that may be unusual for the given location. Inpatient dermatologists should be prepared to manage these potentially unfamiliar dermatologic consequences of climate change.

SUMMARY

Climate change will have widespread effects on the medical field, and inpatient dermatologists will be faced with their own unique set of challenges and practice variations. Practitioners should be familiar with the ongoing and predicted effects of climate change in their locations so that they can readily identify and treat associated conditions, and they should adjust their practice to reduce their carbon footprint and serve as a model for patients to do the same.

Antivirals in medical biodefense

The viruses historically implicated or currently considered as candidates for misuse in bioterrorist events are poxviruses, filoviruses, bunyaviruses, orthomyxoviruses, paramyxoviruses and a number of arboviruses causing encephalitis, including alpha- and flaviviruses. All these viruses are of concern for public health services when they occur in natural outbreaks or emerge in unvaccinated populations. Recent events and intelligence reports point to a growing risk of dangerous biological agents being used for nefarious purposes. Public health responses effective in natural outbreaks of infectious disease may not be sufficient to deal with the severe consequences of a deliberate release of such agents. One important aspect of countermeasures against viral biothreat agents are the antiviral treatment options available for use in post-exposure prophylaxis. These issues were adressed by the organizers of the 16th Medical Biodefense Conference, held in Munich in 2018, in a special session on the development of drugs to treat infections with viruses currently perceived as a threat to societies or associated with a potential for misuse as biothreat agents. This review will outline the state-of-the-art methods in antivirals research discussed and provide an overview of antiviral compounds in the pipeline that are already approved for use or still under development.

Climate change and viral emergence: evidence from Aedes-borne arboviruses

Climate change is leading to increases in global temperatures and erratic precipitation patterns, both of which are contributing to the expansion of mosquito-borne arboviruses and the populations of the mosquitos that vector them. Herein, we review recent evidence of emergence and expansion of arboviruses transmitted by Aedes mosquitos that has been driven in part by environmental changes. We present as a case study of recent work from Córdoba, Argentina, where dengue has been actively emerging in the past decade. We review recent empirical and modeling studies that aim to understand the impact of climate on future expansion of arboviruses, and we highlight gaps in empirical studies linking climate to arbovirus transmission at regional levels.

Temperature-dependent variation in the extrinsic incubation period elevates the risk of vector-borne disease emergence

Identifying ecological drivers of disease transmission is central to understanding disease risks. For vector-borne diseases, temperature is a major determinant of transmission because vital parameters determining the fitness of parasites and vectors are highly temperature-sensitive, including the extrinsic incubation period required for parasites to develop within the vector. Temperature also underlies dramatic differences in the individual-level variation in the extrinsic incubation period, yet the influence of this variation in disease transmission is largely unexplored. We incorporate empirical estimates of dengue virus extrinsic incubation period and its variation across a range of temperatures into a stochastic model to examine the consequences for disease emergence. We find that such variation impacts the probability of disease emergence because exceptionally rapid, but empirically observed incubation - typically ignored by modelling only the average - increases the chance of disease emergence even at the limits of the temperature range for dengue transmission. We show that variation in the extrinsic incubation period causes the greatest proportional increase in the risk of disease emergence at cooler temperatures where the mean incubation period is long, and associated variation is large. Thus, ignoring EIP variation will likely lead to underestimation of the risk of vector-borne disease emergence in temperate climates.

Modeling Temperature Effects on Population Density of the Dengue Mosquito Aedes aegypti

Mosquito density plays an important role in the spread of mosquito-borne diseases such as dengue and Zika. While it remains very challenging to estimate the density of mosquitoes, modelers have tried different methods to represent it in mathematical models. The goal of this paper is to investigate the various ways mosquito density has been quantified, as well as to propose a dynamical system model that includes the details of mosquito life stages leading to the adult population. We first discuss the mosquito traits involved in determining mosquito density, focusing on those that are temperature dependent. We evaluate different forms of models for mosquito densities based on these traits and explore their dynamics as temperature varies. Finally, we compare the predictions of the models to observations of Aedes aegypti abundances over time in Vitòria, Brazil. Our results indicate that the four models exhibit qualitatively and quantitatively different behaviors when forced by temperature, but that all seem reasonably consistent with observed abundance data.