Dengue Prevalence Research Articles

Dengue in Tomorrow: Predictive Insights From ARIMA and SARIMA Models in Bangladesh: A Time Series Analysis.

Dengue fever has been a continued public health problem in Bangladesh, with a recent surge in cases. The aim of this study was to train ARIMA and SARIMA models for time series analysis on the monthly prevalence of dengue in Bangladesh and to use these models to forecast the dengue prevalence for the next 12 months. This secondary data-based study utilizes AutoRegressive Integrated Moving Average (ARIMA) and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models to forecast dengue prevalence in Bangladesh. Data was sourced from the Institute of Epidemiology Disease Control and Research (IEDCR) and the Directorate General of Health Services (DGHS). STROBE Guideline for observational studies was followed for reporting this study. The ARIMA (1,1,1) and SARIMA (1,1,2) models were identified as the best-performing models. The forecasts indicate a steady dengue prevalence for 2024 according to ARIMA, while SARIMA predicts significant fluctuations. It was observed that ARIMA (1,1,1) and SARIMA (1,2,2) (1,1,2) 12 were the most suitable models for prediction of dengue prevalence. These models offer valuable insights for healthcare planning and resource allocation, although external factors and complex interactions must be considered. Dengue prevalence is expected to rise in future in Bangladesh.

Quantitative modelling for dengue and Aedes mosquitoes in Africa: A systematic review of current approaches and future directions for Early Warning System development.

The rapid spread and growing number of dengue cases worldwide, alongside the absence of comprehensive vaccines and medications, highlights the critical need for robust tools to monitor, prevent, and control the disease. This review aims to provide an updated overview of important covariates and quantitative modelling techniques used to predict or forecast dengue and/or its vector Aedes mosquitoes in Africa. A systematic search was conducted across multiple databases, including PubMed, EMBASE, EBSCOhost, and Scopus, restricted to studies conducted in Africa and published in English. Data management and extraction process followed the 'Preferred Reporting Items for Systematic Reviews and Meta-Analyses' (PRISMA) framework. The review identified 30 studies, with the majority (two-thirds) focused on models for predicting Aedes mosquito populations dynamics as a proxy for dengue risk. The remainder of the studies utilized human dengue cases, incidence or prevalence data as an outcome. Input data for mosquito and dengue risk models were mainly obtained from entomological studies and cross-sectional surveys, respectively. More than half of the studies (56.7%) incorporated climatic factors, such as rainfall, humidity, and temperature, alongside environmental, demographic, socio-economic, and larval/pupal abundance factors as covariates in their models. Regarding quantitative modelling techniques, traditional statistical regression methods like logistic and linear regression were preferred (60.0%), followed by machine learning models (16.7%) and mixed effects models (13.3%). Notably, only 36.7% of the models disclosed variable selection techniques, and a mere 20.0% conducted model validation, highlighting a significant gap in reporting methodology and assessing model performance. Overall, this review provides a comprehensive overview of potential covariates and methodological approaches currently applied in the African context for modelling dengue and/or its vector, Aedes mosquito. It also underscores the gaps and challenges posed by limited surveillance data availability, which hinder the development of predictive models to be used as early warning systems in Africa.

Qualitative and optimal control analysis of a two-serotype dengue model with saturated incidence in co-infection

ABSTRACT The arboviral disease dengue is a life-threatening global public health problem due to its high prevalence rate, morbidity and mortality. Recent studies suggest that morbidity during secondary dengue infection is higher than during primary infection. To deepen our understanding, we have explored a two-serotype co-infected dengue model with bilinear incidence for primary infection and saturated incidence for secondary infection. In the model, we have also included four control measures: mosquito bite prevention control, treatment control, vaccine control and mosquito killing control. The existence and local stability of the disease free, serotype II free, serotype I free and endemic equilibrium points have been studied. The effect of inhibitory or awareness factors on disease dynamics has also been exhaustively examined. By using sensitivity analysis we have identified and quantified the most influential parameters to prevent as well as to control the dengue outbreak. To optimize our strategies, we have characterized the time-dependent optimal control to reduce dengue prevalence and the total implementation cost of the aforementioned controls. Efficiency analysis has been done to identify the best effective combination of the applied controls to reduce dengue infection. Mosquito bites with treatment control is the most effective combined strategy to control dengue infection.

A pilot field study on Dengue vectors with locally manufactured inexpensive gravid female traps

High prevalence of Aedes aegypti and Ae. albopictus vectors and dengue incidence as well as the presence of the four dengue virus serotypes underscore the need for effective and simple tools to monitor dengue vectors in Sri Lanka. Field studies were therefore undertaken with inexpensive gravid female trap (GFT) fabricated from local materials in Jaffna city in northern Sri Lanka. The study was initiated in April 2022, and GFT-based mosquito collection was conducted from June 2022 to April 2023. Five blocks of 30 to 40 houses, were selected in areas of high dengue prevalence in Jaffna city. Thirty houses were selected within each block and provided with five traps to be placed indoor and outdoor in each house. Conventional larval indices were determined at the beginning, middle and end of the study. Nine rounds of GFT collections were performed to identify and quantify trapped mosquitoes, their parity, and infection with virus serotypes. A total of 2177 and 3069 Aedes were collected respectively in indoor and outdoor GFTs, during nine rounds of collections and identified at the species level where possible. A total of 679 and 433 Ae. aegypti and Ae. albopictus were collected in indoor traps and 377 and 1288 in outdoor traps respectively. Adult and larval indices decreased respectively by 50% and 100% by the end of the study. Parous mosquitoes comprised 93% (of 120) and 94% (of 288) of the collected Ae. aegypti and Ae. albopictus respectively. In 110 pools of female Ae. aegypti and Ae. albopictus screened for virus serotype by PCR, five pools of Ae. aegypti and six pools of Ae. albopictus from both indoor and outdoor collections were positive for DENV-2. GFTs fabricated with locally available and inexpensive materials described here can be effective for monitoring the prevalence of Aedes vector species, parity and dengue virus infection status. The larval indices suggest that the use of GFTs can contribute to reducing dengue transmission.

Spatial mapping of dengue fever prevalence and its association with geo-climatic factors in Lahore, Pakistan.

A vector-borne disease of concern for global public health, dengue fever has been spreading its endemicity and several cases in recent years, particularly in Lahore Pakistan. Dengue transmission is influenced by geo-climatic conditions. This study aimed to map the spatial prevalence of dengue fever in Lahore and its association with geo-climatic factors during the epidemic of the year 2021. In this study, geo-climatic factors that could potentially encourage the growth of the virus are chosen for this study, and their temporal and spatial changeability relate to dengue cases. The objective of this study is to use meteorological, satellite data and Geographic Information System (GIS) techniques to map dengue outbreaks and identify the risk-prone areas by relating geo-climatic factors with dengue outbreaks. The dengue patients and their locations data were collected from the Directorate General of Health Services (DGHS) Lahore. This study uses Google Earth and Landsat-8 OLI/TIRs images to extract geo-climatic and land use parameters. The dot density maps technique was used to represent the spatiotemporal distribution of dengue cases. The hotspot analysis was applied to show the hotspots of dengue cases in district Lahore at the Union Council (UC) level. The Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI), built-up area, population density, precipitation, and Land Surface Temperature (LST) are the factors employed. In this study, correlation was performed to test the significance between precipitation and the prevalence of dengue fever in Lahore. The results show that the incidence and prevalence of dengue fever month-wise at the UC level in Lahore. The distribution pattern of dengue outbreaks in the Lahore area and its demographic factors were found to be associated. It concludes that the increase in the spread of dengue fever is associated with the monsoon rains. The prevalence of dengue is associated with water bodies and high land surface temperature, but it does not represent any significant relation with vegetation cover and land use in Lahore during the year 2021. The study pinpointed the locations that are most susceptible and require care to prevent such outbreaks in the future.

Dengue Hemorrhagic Fever in Quang Nam Province (Vietnam) from 2020 to 2022-A Study on Serotypes Distribution and Immunology Factors.

Background: Dengue hemorrhagic fever (DHF) is the most prevalent and fastest-growing vector-borne disease globally, with symptoms ranging from mild to severe and, in some cases, fatal. Quang Nam province in Vietnam can serve as a model for dengue epidemiological study, as it is an endemic region for DHF with a tropical climate, which significantly constrains the health system. However, there are very few epidemiological and microbiological reports on Dengue virus (DENV) serotypes in this region due to the limited availability of advanced surveillance infrastructure. Aims of the study: This study aims to (1) assess the PCR positivity rates among hospitalized patients with clinical Dengue presentation; (2) identify the circulating DENV serotypes; and (3) assess the impact of secondary DENV infections on outbreak severity by detecting the presence of DENV-specific IgG antibodies in the plasma of DENV-infected patients. Materials and methods: Blood samples from patients clinically diagnosed with DHF and admitted to Quang Nam General Hospital (2020-2022) were analyzed. RNA extraction was performed using the NKDNA/RNAprep MAGBEAD kit, followed by Multiplex Reverse Transcription real-time Polymerase Chain Reaction (MLP RT-rPCR) for DENV detection and serotype identification. Positive samples were further tested for DENV-specific IgG antibodies using an enzyme-linked immunosorbent assay (ELISA). Results: The PCR positivity rate among hospitalized patients was approximately 68% throughout the study period. A significant shift in DENV serotypes was observed, with DENV-2 initially dominant and later giving way to DENV-1. IgG was detected in nearly half of the MPL RT-rPCR-positive samples, indicating secondary DENV infections. Conclusions: Our study highlights persistent dengue prevalence and dynamic shifts in DENV serotypes in Quang Nam province, emphasizing the need for improved diagnostic strategies and timely sample collection. The significant serotype shifts and the presence of IgG in hospitalized patients suggest potential severe outcomes from recurrent DENV infections, possibly linked to antibody-dependent enhancement (ADE) effect, underscoring the importance of advanced surveillance, vector control, vaccination campaigns, and public education to predict and prevent future DHF epidemics.

Impact of deforestation and climate on spatio-temporal spread of dengue fever in Mexico

Dengue prevalence results from the interaction of multiple socio-environmental variables which influence its spread. This study investigates the impact of forest loss, precipitation, and temperature on dengue incidence in Mexico from 2010 to 2020 using a Bayesian hierarchical spatial model. Three temporal structures—AR1, RW1, and RW2—were compared, with RW2 showing superior performance. Findings indicate that a 1 % loss of municipal forest cover correlates with a 16.9 % increase in dengue risk. Temperature also significantly affects the vectors' ability to initiate and maintain outbreaks, highlighting the significant role of environmental factors. The research emphasizes the importance of multilevel modeling, finer temporal data resolution, and understanding deforestation causes to enhance the predictability and effectiveness of public health interventions. As dengue continues affecting global populations, particularly in tropical and subtropical regions, this study contributes insights, advocating for an integrated approach to health and environmental policy to mitigate the impact of vector-borne diseases.

Dengue dynamics in Nepal: A Caputo fractional model with optimal control strategies

An infectious disease called dengue is a significant health concern nowadays. The dengue outbreak occurred with a single serotype all over Nepal in 2023. In the tropical and subtropical regions, dengue fever is a leading cause of sickness and death. Currently, there is no specified treatment for dengue fever. Avoiding mosquito bites is strongly advised to reduce the likelihood of controlling this disease. In underdeveloped countries like Nepal, the implementation of appropriate control measures is the most important factor in preventing and controlling the spread of dengue illness. The Caputo fractional dengue model with optimum control variables, including mosquito repellent and insecticide use, investigates the impact of alternative control strategies to minimize dengue prevalence. Using the fixed point theorem, the existence and uniqueness of a solution will be demonstrated for the problem. Ulam-Hyers stability, disease-free equilibrium point stability, and basic reproduction number are studied for the proposed model. The model is simulated using a two-step Lagrange interpolation technique, and the least squares method is used to estimate parameter values using real monthly infected data. We then analyze the sensitivity analysis to determine influencing parameters and the control measure effects on the basic reproduction number. The Pontryagin Maximum Principle is used to determine the optimal control variable in the dengue model for control strategies. The present study suggests that the deployment of control measures is extremely successful in lowering infectious disease incidences. Which facilitates the decision-makers to practice rigorous evaluation of such an epidemiological scenario while implementing appropriate control measures to prevent dengue disease transmission in Nepal.

Dengue fever mapping in Bangladesh: A spatial modeling approach

AbstractBackgroundEpidemics of the dengue virus can trigger widespread morbidity and mortality along with no specific treatment. Examining the spatial autocorrelation and variability of dengue prevalence throughout Bangladesh's 64 districts was the focus of this study.MethodsThe spatial autocorrelation is evaluated with the help of Moran and Geary . Local Moran was used to detect hotspots and cold spots, whereas local Getis Ord G was used to identify only spatial hotspots. The spatial heterogeneity has been detected using various conventional and spatial models, including the Poisson‐Gamma model, the Poisson‐Lognormal Model, the Conditional Autoregressive (CAR) model, the Convolution model, and the BYM2 model, respectively. These models are implemented using Gibbs sampling and other Bayesian hierarchical approaches to analyze the posterior distribution effectively, enabling inference within a Bayesian context.ResultsThe study's findings show that Moran and Geary analysis provides a substantial clustering pattern of positive spatial autocorrelation of dengue fever (DF) rates between surrounding districts at a 90% confidence interval. The Local Indicators of Spatial Autocorrelation cluster mapped spatial clusters and outliers based on prevalence rates, while the local Getis‐Ord G displayed a thorough breakdown of high or low rates, omitting outliers. Although Chattogram had the most dengue cases (15,752), Khulna district had a higher prevalence rate (133.636) than Chattogram (104.796). The BYM2 model, determined to be well‐fitted based on the lowest Deviance Information Criterion value (527.340), explains a significant association between spatial heterogeneity and prevalence rates.ConclusionThis research pinpoints the district with the highest prevalence rate for dengue and the neighboring districts that also have high risk, allowing government agencies and communities to take the necessary precautions to mollify the risk effect of DF.

Analysis of temperature, humidity, rainfall, and wind velocity on dengue hemorrhagic fever in Bandung municipality

The trend of dengue hemorrhagic fever prevalence every year continues to show an increase and number of deaths. This is due to an increase in the population of aedes aegypti mosquitoes. Climate change has the potential to affect mosquito-borne diseases, including dengue fever, which is a vulnerability for residents in Bandung Municipality. This research aims to analyse the relationship between temperature, humidity, rainfall, and wind velocity with dengue hemorrhagic fever in Bandung Municipality. The methodology research used in this study is descriptive analysis with a cross-sectional approach. This research was conducted in Bandung Municipality. The study samples were taken from data on dengue hemorrhagic fever sufferers, as well as data on temperature, humidity, rainfall, and wind speed. This study used secondary data. The data collected is in the form of data on temperature, humidity, rainfall, and wind speed, and the number of cases. To assess the correlation between variables using the person correlation test. To test the effect of all four variables simultaneously on the incidence of dengue hemorrhagic fever using a linear regression test. Average value of air temperature is 25.8°C, air humidity is 69.9%, rainfall is 201.5 mm, and the wind velocity is 1.8 knots. The prevalence of dengue hemorrhagic fever is 232.5 cases. There is a significant relationship between humidity with dengue hemorrhagic fever prevalency (p = 0.018, r = 0.873). Wind velocity with dengue hemorrhagic fever prevalency (p = 0.018, r = 0.629). The result of the coefficient of determination test on temperature, humidity, rainfall, and wind velocity with DHF cases is R2 = 0.745. The increase in dengue prevalence in Bandung City occurred from January to June, the decrease in prevalence occurred from July to December. Variations in temperature, humidity, rainfall and wind speed can simultaneously affect the incidence of dengue fever in Bandung. Therefore, in the future it is necessary to increase mosquito nest eradication activities to prevent dengue transmission considering that this disease has the potential to spread at any time.

Land use and meteorological influences on dengue transmission dynamics in Dhaka city, Bangladesh

BackgroundDengue fever, a viral illness spread mostly by Aedes mosquitoes, continues to pose a substantial public health issue in Dhaka city, Bangladesh. In Dhaka, climatic and socio-demographic factors like population density affect the spread of dengue. The dengue indexes are greatest in the residential mixed zone. Numerous environmental parameters, such as temperature, relative humidity, rainfall, and the air pollution index, have been linked to mosquito larvae, and dengue prevalence is correlated with urbanization, decreased vegetation, and population expansion.MethodsBy using an extensive dataset that encompasses a range of years, we use spatial and temporal analytic methodologies to investigate the correlation between land use attributes, climatic variables, and the occurrence of dengue fever. To better understand the dynamics of dengue, the built environment and climatic factors are treated as independent variables in this study. ArcPy is a Python package that facilitates here for geographic data analysis and ArcMap 10.7 also used for visualizing spatial data.ResultsThe results of our study demonstrate that land use significantly influences the spatial patterns of Dengue incidence in Dhaka city. The dengue hotspot Thana are identified and these are Badda, Jatrabari, kadamtali, Mirpur, Mohammadpur, Sobujbagh, Shyampur, Tejgoan, Dhanmondi and Uttara. All of these areas’ population density and residential use as land use is higher than the other Thana of Dhaka city. There exists a significant correlation between climatic characteristics, such as temperature (0.25), rainfall (.803), specific humidity (0.74), relative humidity (0.76), wind speed (0.4) and Dengue incidence patterns. This research emphasizes the structural use and climatic relationship in Dengue epidemics, with climatic conditions playing a significant role as drivers of these variations.ConclusionsThis research demonstrates the complex relationship between land use, meteorological factors, and the spread of Dengue fever in Dhaka city. The results of this study have significant significance for several domains, including urban planning, public health measures, and vector control tactics. A comprehensive understanding of the temporal and geographical patterns of dengue transmission might aid in the development of accurate and effective prevention measures intended to lessen the effects of dengue in cities, such as Dhaka.

Dengue Cases Presenting to the Emergency Department of a Tertiary Care Hospital in Late 2021: A Cross-Sectional Study in Karachi.

Objectives: Dengue Fever (DF) is an arboviral disease caused by the Dengue virus (DENV). This study aims to assess the association of dengue prevalence with patients' residential areas and hematological laboratory findings (Total platelet count, immunoglobulins, and dengue antigens) during COVID-19 pandemic. Methods: A retrospective study was conducted at the Emergency department of Jinnah Postgraduate Medical Center, Karachi from October to December 2021. All the patients irrespective of their ages presenting to the ED with either of the following complaints: fever; GIT problems; vomiting; body ache; bleeding were included in our study. Results: Our study comprised 189 patients in total in which the females (n = 172) outnumbered the males (n = 17). Out of all, 84.7% of the patients were febrile having a low-grade fever on average. Korangi district had the most dengue cases, while Keamari had the fewest. There was no significant association reported between mean platelet count, mean TLC, and mean hemoglobin levels with dengue positivity. Conclusion: There is a concerning rise in DF cases in Karachi, particularly in the Korangi district. Despite the COVID-19 pandemic, DF demands urgent attention.

Determinants and prevalence of symptomatic dengue fever among adults in the Central Region of Burkina Faso: a hospital-based cross-sectional study

BackgroundDengue fever (DF) is a significant public health concern in Burkina Faso, particularly in the Central Region, previously endemic for malaria. However, limited research has focused on dengue prevalence and associated factors among adult febrile patients in this region. This study aimed to estimate the prevalence of symptomatic dengue fever among adults and identify the sociodemographic and clinical determinants of the disease.MethodsA seroepidemiological cross-sectional study was conducted in the Central Region of Burkina Faso, through a three-stage sampling. Five health facilities, one from each of the region five districts, were purposively selected. Febrile patients aged 16 and older, suspected of having dengue, were included in the study, after consenting. Bivariate analyses and multivariate binary logistic regression were done at a 5% confidence level.ResultsA total of 637 patients between the ages of 16 and 90 years were included. Most of the participants were females (58.71%). Most dengue cases resided in Arrondissement 4 (59.62%), or were present in the Arrondissement 4 at daytime during the previous days (51.92%). 52.90% of the participants knew of dengue. Dengue prevalence was estimated at 8.16% (95% CI: 6.16%-10.57%). The most frequent markers for dengue were immunoglobulins M detected in 4.40% (2.94%-6.29%), followed by Antigen NS1 at 4.24% (95% CI: 2.81%-6.11%). The Antigen NS1 marker was associated with myalgia (p = 0.024), vomiting (p < 0.001), hemorrhagic manifestations (p = 0.001), and anorexia (p < 0.001). Staying at Arrondissement 4 (vs staying at Saaba) during daytime (aOR = 2.36 95% CI: 1.03–5.45; p = 0.044) significantly increased the odds of dengue. Dengue cases were about 3 times more likely to have vomited (aOR = 2.99 95% CI: 1.58–5.64; p = 0.001). Participants knowing of dengue (aOR = 0.53 95% CI: 0.29–0.98; p = 0.042) and those coinfected with malaria (aOR = 0.28 95% CI: 0.14–0.57; p < 0.001) instead had reduced odds of dengue.ConclusionThe study revealed a relatively high prevalence of symptomatic dengue fever among adults in the Central Region of Burkina Faso in 2022. These findings emphasize the need for continuous surveillance and targeted control measures. The low coinfection of dengue and malaria warrants further investigation.

Outbreaks of dengue in India since 2012

Dengue is an arthropod - borne virus which belongs to Flaviviridae family cause a range of different illness from mild symptoms to severe deadly Dengue Hemorrhagic fever/Dengue shock syndrome. Dengue is a self-limiting disease. The sharp raise in population, inadequate steps to eradicate mosquito breeds and Climatic changes – Delayed monsoon and heavy rainfall are the most important factors that leads to the drastic increase of Dengue cases in India. Approximately 94198 cases and 91 deaths were reported in India. According to World Health Organization Dengue is considered as a major global public health challenge for tropical and subtropical nations. This article summarizes the State wise dengue burden, Prevalence and Incidence. This article also includes some Global strategies for dengue prevention and control.

Attrition in serum anti-DENV antibodies correlates with high anti-SARS-CoV-2 IgG levels and low DENV positivity in mosquito vectors-Findings from a state-wide cluster-randomized community-based study in Tamil Nadu, India.

The decline in dengue incidence and/or prevalence during the COVID-19 pandemic (2020-22) appears to be attributed to reduced treatment-seeking rates, under-reporting, misdiagnosis, disrupted health services and reduced exposure to mosquito vectors due to prevailing lockdowns. There is limited scientific data on dengue virus (DENV) disease during the COVID-19 pandemic. Here, we conducted a community-based, cross-sectional, cluster-randomized survey to assess anti-DENV and anti-SARS-CoV-2 seroprevalence, and also estimated the spatial distribution of DENV-positive aedine mosquito vectors during the COVID-19 pandemic across all the 38 districts of Tamil Nadu, India. Using real-time PCR, the prevalence of DENV in mosquito pools during 2021 was analyzed and compared with the previous and following years of vector surveillance, and correlated with anti-DENV IgM and IgG levels in the population. Results implicate that both anti-DENV IgM and IgG seroprevalence and DENV positivity in mosquito pools were reduced across all the districts. A total of 13464 mosquito pools and 5577 human serum samples from 186 clusters were collected. Of these, 3.76% of the mosquito pools were positive for DENV. In the human sera, 4.12% were positive for anti-DENV IgM and 6.4% for anti-DENV IgG. While the anti-SARS-CoV-2 levels significantly correlated with overall DENV seropositivity, COVID-19 vaccination status significantly correlated with anti-DENV IgM levels. The study indicates a profound impact of anti-SARS-CoV-2 levels on DENV-positive mosquito pools and seropositivity. Continuous monitoring of anti-DENV antibody levels, especially with the evolving variants of SARS-CoV-2 and the surge in COVID-19 cases will shed light on the distribution, transmission and therapeutic attributes of DENV infection.

Mapping of the Oviposition Ability, Survival Rate, and Distribution of Dengue Vector in Bengkulu City, Indonesia

Vector surveillance is pivotal for dengue prevalence. The oviposition ability, survival rate, and distribution of dengue vector species can indicate the population density and are components of mosquito survival strategies. The density of dengue vectors is influenced by altitude, population density, water sources, and vegetation characteristics in their breeding habitats. This study aims to determine the oviposition ability, survival rate, and distribution of dengue vectors in Bengkulu City. This study employed a quantitative method with a descriptive observational design. Data were obtained by collecting Aedes spp. eggs from 67 urban villages in Bengkulu City. The survival rate was determined through colonization, and the distribution of mosquito species was analyzed based on the mosquitoes resulting from colonization. Beringin Raya was identified as the urban village with the highest oviposition ability, while Kandang was identified as the lowest. The highest survival rate of dengue vectors was found in Jalan Gedang, while the lowest was found in Sumber Jaya, Muara Dua, Padang Jati, and Tengah Padang. Aedes aegypti dominated 36 urban villages, while Aedes albopictus dominated 26 urban villages. In conclusion, dengue vectors were distributed across all urban villages in Bengkulu City, with Aedes aegypti being the dominant species.

Combatting Malaysia's Dengue Outbreaks with Auto-Dissemination Mosquito Traps: A Hybrid Stochastic-Deterministic SIR Model

Classical mosquito control methods (e.g. chemical fogging) struggle to sustain long-term reductions in mosquito populations to combat vector-borne diseases like dengue. The Mosquito Home System (MHS) is an auto-dissemination mosquito trap, that kills mosquito larvae before they hatch into adult mosquitoes. A novel hybrid stochastic-deterministic model is presented, that successfully predicts the effect of deploying MHSs within high-rise flats in Selangor, Malaysia. Stochastic SIR (Susceptible-Infected-Recovered) equations (flats) are paired with an existing deterministic SIR model (wider Kuala Lumpur population). Model predictions provide excellent agreement with data from a 44 week MHS trial within the flats. The stochastic model is validated as a powerful tool for predicting short- and long-term impacts of deploying this style of trap within similar environments. Significant, sustainable reductions in mosquito populations are predicted when the MHS is active: with a mean of 9 (95% Uncertainty Range (UR): 1; 30) during the 44 week trial period, compared to 35 (95% UR: 1; 234) dengue cases with no MHSs. Long-term predictions for endemic equilibrium show MHSs significantly narrow the mosquito population distribution and reduce dengue prevalence: from a mean of 5 (95% UR: 0; 52) (no MHS), to 1 (95% UR: 0; 8) dengue cases annually (with MHS).

A non-integer order model for Zika and Dengue co-dynamics with cross-enhancement

A novel fractional derivative model with nine compartments is formulated to investigate the transmission dynamics of zika and dengue co-infection. The Atangana–Baleanu fractional derivative in the Caputo sense was employed. The conditions for a unique solution are identified, and the solutions’ positivity and boundedness are demonstrated. The disease-free equilibrium point (DFE) and basic reproduction number, R0, were obtained. The DFE was shown to be locally asymptotically stable when the basic reproduction number is less than one. Zika-associated reproduction number, R0z, and dengue-associated reproduction number, R0d, were estimated to be 1.0144 and 1.1724, respectively. The system was shown to be generalized Ulam Hyers–Rassias stable, and the Adam–Bashforth method was used to provide its’ numerical solution. Sensitivity analysis using the Latin Hyper-cube Sampling (LHS) and Partial Rank Correlation Coefficient (PRCC) (|PRCC|> 0.45) with 200 runs was carried out using various variables as response functions per time. The most significant parameters were found to be zika human-to-human transmission rate, βhz1, vector death rate, μv, zika recovery rate, γhz1 and dengue vector-to-human transmission rate, βhd. Real data from Espirito Santo in Brazil is used to validate the model and fit needed parameter values. Numerical simulations illustrated the impact of varying the fractional order derivative, recovery rates, transmission rates, and cross-enhancement parameters on the infected human compartments. The zika Human-to-human transmission rate, βhz1, was found to be a very significant parameter in the control of zika disease transmission. Increasing the vector death rate, μv, was more important in curbing dengue prevalence and incidence than the attainment of recovery from the dengue disease, and the absence of the zika Vector-to-human transmission rate, βhz3, was almost insignificant in the presence of the zika Human-to-human transmission rate, βhz1, for disease eradication. This study suggested control measures and strategies to decrease the dengue and zika human-to-human transmission rates.

Increasing prevalence of malaria and acute dengue virus coinfection in Africa: a meta-analysis and meta-regression of cross-sectional studies

BackgroundMalaria and dengue fever are the leading causes of acute, undifferentiated febrile illness. In Africa, misdiagnosis of dengue fever as malaria is a common scenario. Through a systematic review of the published literature, this study seeks to estimate the prevalence of dengue and malaria coinfection among acute undifferentiated febrile diseases in Africa.MethodsRelevant publications were systematically searched in the PubMed, Cochrane Library, and Google Scholar until May 19, 2023. A random-effects meta-analysis and meta-regression were used to summarize and examine the prevalence estimates.ResultsTwenty-two studies with 22,803 acute undifferentiated febrile patients from 10 countries in Africa were included. The meta-analysis findings revealed a pooled prevalence of malaria and dengue coinfection of 4.2%, with Central Africa having the highest rate (4.7%), followed by East Africa (2.7%) and West Africa (1.6%). Continent-wide, Plasmodium falciparum and acute dengue virus coinfection prevalence increased significantly from 0.9% during 2008–2013 to 3.8% during 2014–2017 and to 5.5% during 2018–2021 (p = 0.0414).ConclusionThere was a high and increasing prevalence of malaria and acute dengue virus coinfection in Africa. Healthcare workers should bear in mind the possibility of dengue infection as a differential diagnosis for acute febrile illness, as well as the possibility of coexisting malaria and dengue in endemic areas. In addition, high-quality multicentre studies are required to verify the above conclusions.Protocol registration number: CRD42022311301.

An ecological assessment of the potential pandemic threat of Dengue Virus in Zhejiang province of China

Background and AimDengue fever, transmitted by Aedes mosquitoes, is a significant public health concern in tropical and subtropical regions. With the end of the COVID-19 pandemic and the reopening of the borders, dengue fever remains a threat to mainland China, Zhejiang province of China is facing a huge risk of importing the dengue virus. This study aims to analyze and predict the current and future potential risk regions for Aedes vectors distribution and dengue prevalence in Zhejiang province of China.MethodWe collected occurrence records of DENV and DENV vectors globally from 2010 to 2022, along with historical and future climate data and human population density data. In order to predict the probability of DENV distribution in Zhejiang province of China under future conditions, the ecological niche of Ae. aegypti and Ae. albopictus was first performed with historical climate data based on MaxEnt. Then, predicted results along with a set of bioclimatic variables, elevation and human population density were included in MaxEnt model to analyze the risk region of DENV in Zhejiang province. Finally, the established model was utilized to predict the spatial pattern of DENV risk in the current and future scenarios in Zhejiang province of China.ResultsOur findings indicated that approximately 89.2% (90,805.6 KM2) of Zhejiang province of China is under risk, within about 8.0% (8,144 KM2) classified as high risk area for DENV prevalence. Ae. albopictus were identified as the primary factor influencing the distribution of DENV. Future predictions suggest that sustainable and “green” development pathways may increase the risk of DENV prevalence in Zhejiang province of China. Conversely, Fossil-fueled development pathways may reduce the risk due to the unsuitable environment for vectors.ConclusionsThe implications of this research highlight the need for effective vector control measures, community engagement, health education, and environmental initiatives to mitigate the potential spread of dengue fever in high-risk regions of Zhejiang province of China.