Dengue Fever Cases Research Articles

A Novel Structure Optoelectronic Biosensor for Detection of Infectious Diseases Using SALP Swarm Optimized Artificial Neural Network Technique

In this study, we detail the use of a small, label-free optoelectronic biosensor for the detection of anti-dengue antibodies in human serum samples. The system consists of a vertical-cavity surface-emitting laser that can be tuned, a guided-mode resonant sensor surface, and two silicon pin detectors. After showing adequate sensitivity in a clinically relevant experiment, researchers hypothesized that this cutting-edge biosensor could serve as a novel platform for the development of efficient point-of-care diagnostic techniques for the identification of infectious diseases. Humans are susceptible to one of the world’s most common and contagious diseases, dengue fever, which is spread by the Aedes albopictis mosquito. Human deaths were also a direct outcome of the widespread increase in Dengue fever cases. A shortage of medical professionals and healthcare facilities only made matters worse. In order to achieve this goal, it will be necessary to employ archaic medical technologies. Recent innovations like Fog Computing and the success of remote healthcare in real time, Cloud Computing, and the Internet of Things have opened up new frontiers in technology (IoT). In this research, we proposed a new method for diagnosing dengue disease. Information gathered from those who have been afflicted by a disease will be shared with higher authorities. Various IoT devices compile comprehensive reports on each and every patient. Once medical history is gathered, the patient’s whereabouts must be ascertained. Sensors connected to the internet are used to gather information on the weather, the location, the effectiveness of medications, the safety of the surrounding environment, and the patients’ states of health. The fog computing layer is the bridge between IoT sensors and cloud servers. Two primary functions of the fog computing layer are the creation of notifications and the categorization of users’ health conditions. Dengue fevers are diagnosed using an Artificial Neural Network (ANN) trained with the Salp Swarm Optimization method Salp swarm algorithm (SSA). The dataset will be analyzed using an Internet of Things (IoT) scenario built with the Java simulator CupCarbon U-one 3.8.2. The proposed method achieves competitive or better outcomes than the state-of-the-art alternatives.

Effectiveness Comparison Of Solution Purut Lime Leaves (Citrus Hystrix) And Basil Leaves (Ocimum Sanctum) Toward Aedes Spp Larvae Mortality

Nowadays, the cases of dengue hemorrhagic fever are progressively increasing and necessitating control. One of the easiest controls in breaking the life cycle of Aedes spp. mosquitoes is to kill mosquito larvae using plants as natural larvacides are environmentally friendly. One of them is using purut lime leaves and basil leaves. The study aims to determine the effectiveness comparison of solution purut lime leaves and basil leaves toward Aedes spp. larvae mortality. This research method is a true experiment with a Post-Test Only Control Group design. It is also followed by concentration at control (0%), 1,5%, 2,5%, 3,5%, 4,5%, and 5,5% with 4 repetitions. The sample was 1.200 instar Aedes spp. III larvae. The results showed the effectiveness of the kaffir lime leaf solution was at the lowest concentration of 3.5% with the mortality of 18 Aedes spp. larvae and the effective concentration of basil leaves was 4.5% with 15 larvae mortality. From an economic and availability perspective, basil leaves are easier to find, making it easier to apply. This makes it easier to apply. Water reservoirs are difficult to clean outside the home.

THE IMPACT OF INTERNATIONAL TOURIST ARRIVALS ON ECONOMIC GROWTH UNDER DENGUE FEVER RISK IN MALAYSIA

Dengue fever has long been a community health problem in tropical countries. Dengue virus is a crucial cause of disease in international tourists, with a rising number of them returning from dengue‐endemic countries infected with dengue fever. This study analyses the impact of international tourist arrivals on economic growth moderated by dengue fever cases in Malaysia from 2014 until 2020. This study was carried out using secondary monthly data for dengue fever cases, gross domestic product (GDP), and international tourist arrivals. A correlation test was used to analyse the correlation between the independent, dependent and moderating variables. Granger causality test was employed to determine the causality between the selected three variables, dengue fever cases, international tourist arrivals, and economic growth. The results reveal a significant correlation between dengue fever cases, tourist arrivals, and economic growth. Between 2017 and 2018, higher international tourist arrivals led to lower economic growth under dengue disease hazards in Malaysia. Furthermore, dengue fever risk is found to have a positive relationship with international tourist arrivals and vice versa. The findings show a causality effect between the selected variables. The selected three indicators drive each other in the period study. In line with the government’s strategy to promote the Malaysian tourism industry, prevention and recovery policies should be planned considering the number of dengue cases and economic factors.

Performance Analysis of the Hybrid Voting Method on the Classification of the Number of Cases of Dengue Fever

Dengue hemorrhagic fever (DHF) is a health problem in Indonesia. The region in Indonesia that has the highest number of cases in West Java with the highest ranking with 10,772 cases. The city of Bandung is recorded to have the highest number of cases at this time, namely 4,424 cases. Dengue fever can be caused by high rainfall. Judging from the high number of cases and fluctuations that occur, it is necessary to predict the spread of the disease so that in the future it can be anticipated by the government. Prediction of the spread of dengue fever in the city of Bandung using various classification algorithms has been done. Therefore, the author wants to make a new breakthrough by using hybrid ensemble learning using a hard voting method from three classification methods, namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Decision Tree (DT). Using the Bandung City DHF disease dataset from 2012 to 2018. The results obtained using the Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Decision Tree (DT) were 84%, 87%, 79%. to improve the classification accuracy of the three methods using a hybrid classification with the hard voting method to get 91% results.

Uncovering of Anti-dengue Molecules from Plants Prescribed for Dengue: A Computational Investigation

Dengue fever is a tropical disease spread worldwide, transmitted by the mosquito Aedes aegypti. It affects 100 million people worldwide every year and half a million cases of dengue hemorrhagic fever are registered. At present, it poses sever health burden as combined infections of COVID-19. Currently, as a combined infection with COVID-19, it is becoming a serious health burden. To identify the active molecule, Maestro V12.7 was used with different tools including LigPrep, Grid Generation, SiteMap, Glide XP Docking, Pharmachophores and MM-GBSA. The UNRESS tool was also used to assess the protein stability with this dengue protein. The docking result showed that all examined phytocomponents except berberine and -(+)-l-alliin had good docking scores of -8.577 (azadirachtin), -8.112 (curcumin), -7.348 (apigenin) and -6.028 (andrographolide). However, berberine and -(+)-l-alliin possessed good hydrogen-bonding interactions with RdRp. In addition, molecular dynamic simulations demonstrate that the complex of azadirachtin and dengue protein has a solid understanding of the precise interactions. As per the research results, the present research suggests that this is the first statement of azadirachtin against NS5 RNA-dependent RNA polymerase domain (RdRp), despite extensive research on this molecule in previous investigations. Furthermore, we anticipate that molecules such as curcumin, apigenin, and andrographolide would show beneficial effects while in vitro and in vivo studies are conducted on virally related objects. Since we performed ADMET and pharmacokinetic properties in this research, we feel that the phytochemicals of the screened anti-dengue molecules may not need to be evaluated for toxicological effects.

Dengue fever with atypical presentation in a tertiary care center in North India: Case series

Dengue fever is a dreaded arboviral infection of utmost global importance having 4 serotypes: DENV1, 2, 3, and 4. Dengue fever and severe dengue are the two clinical spectrums commonly classified. However, unusual or atypical manifestations are often overlooked causing significant fatality. This series of 6 case of dengue fever fill the lacunae of knowledge gaps. Case presentation: All the 6 cases presented to Max Super Specialty Hospital, Vaishali from august to October of 2021. The mean age does 40.83 years (range 23-69 years) comprise 5 male and 1 female. The group had life threatening complications like ischemic stroke, intracranial hemorrhage, subdural hematoma, encephalitis, cardiomyopathy, acute myocardial infraction, acute kidney injury, acute liver failure, which were atypical manifestations in dengue patients. Conclusions: Dengue is one the biggest challenge to public health all over world, especially developing countries like India. Dengue fever presenting with atypical manifestations cause delay in diagnosis, leading to fatal outcome. Clinicians should be well aware of these atypical manifestations of such a common arboviral disease as these are often underreported and overlooked.

Dengue Fever Dynamics in Bali, Indonesia 2010-2018: An Interplay of Population Density and Climatic Factors

Dengue Fever (DF) incidence in Bali has been the highest in Indonesia for decades. This study describes the annual distribution of DF and analyzes its association with population density, number of rainy days, and average humidity during 2010-2018 at the district level. The choropleth maps and Poisson regression were employed to provide geographical distribution and quantify the association. The P, 95% confidence interval (CI), and Akaike Information Criterion (AIC) were adopted to assess the significance and the goodness of the association. During 2010-2018 there were 55 215 new DF cases notified. The annual incidence of dengue cases in Bali increased with IRR: 1.000186 (95% CI:1.0000183:1.000189) for every increment of population density per kilometers square and increased by IRR: 1.01043 (95% CI: 1.01019: 1.01078) for every additional one rainy day annually. The dengue cases also increased with IRR 1.0172 (95% CI: 1.0137: 1.0208) for every 1% increase in average humidity. Population density and climate factors are positively associated with dengue cases incidence in Bali from 2010 to 2018. The results underline the urgency of integrating population dynamics and climatic determinants into the DF control program and customizing the intervention program based on local characteristics.

An Audit of Clinical Cases of Dengue Fever and the Usage of Platelets in Such Cases in a Tertiary Care Hospital in Hyderabad

Background and Objectives: Dengue is an acute self-limited systemic viral infection caused by the dengue virus of the family Flaviviridae. The incidence of dengue fever has been increasing for the past few years and dengue has become a global problem. The current data required for further improving the treatment policies are scanty. Our study aims to capture the demographic and clinical characteristics of the patients enrolled in the study, to see any correlation between thrombocytopenia and bleeding tendencies and other transfusion-related parameters. Methods: The study is a prospective cohort study. All seropositive dengue cases were included in the study. A format was prepared for documenting the demographic data, history, clinical characteristics, spectrum of the disease, the laboratory details of the patient (platelet count, prothrombin time, activated partial thromboplastin time, Hematocrit, and indication). All the transfusion requirement data were collected from the blood center registers. Overall mortality in the study group, number of hospital readmissions, and episodes of exacerbation of symptoms was recorded separately. Results: A total of 270 cases were included in the audit who fulfilled the inclusion and exclusion criteria. The median age of the patient pool was 27 (4–66 years range). Twenty-six percent of the cases developed hemorrhages. Eighty-four single-donor platelets (SDPs) and 340 random-donor platelets (RDPs) were used. A mean of 270 ml of products was transfused per patient. The mortality rate was 0.8%. The mean duration of hospitalization was 1 week. In 72% of cases, platelet count was restored in single-unit transfusion. Ninety-nine percent of the product utilization were within the guidelines recommended. Conclusion: A good monthly audit of blood product utilization is a good guide for treatment. Quality control and rational use of SDPs and RDPs are important in sick and thrombocytopenic patients resulting in better clinical outcomes.

The application of geographic information system for dengue epidemic in Southeast Asia: A review on trends and opportunity.

The infectious disease dengue hemorrhagic fever remains an unresolved global problem, with climatic conditions and the location of areas located at the equator more often infected with dengue fever. Various modeling approaches have been employed for the development of a dengue risk map. The geographic information system approach was used as an instrument in applying mathematical algorithms to process field vector data into a preventive objective which is studied, then the application of remote sensing provides spatial-temporal data related to land use/land cover data sources as other variable categories. Map of hotspots for dengue fever cases is used to identify the risk of dengue fever areas by applying various complex methodologies, analysis, and visualization of advanced data are needed for its application in public health. In the last 10 years, the increase in the publication of dengue hemorrhagic fever in Southeast Asia in reputable international journals has increased significantly.

Relationship Between Rainy Day and Sunshine Duration with Dengue Hemorrhagic Fever Incidence in City of Yogyakarta

Introduction – Dengue fever is a disease that often occurs in tropical countries, including Indonesia. DHF is caused by the dengue virus from the Flaviviridae family and infects through the Aedes aegypti or Aedes albopictus mosquitoes. DHF transmission is related to the survival capacity, behavior, and habitat of mosquito as vectors, therefore it may be influenced by climatic factors such as the number of rainy days and the sunshine duration. Purpose – The aim of the study was to determine whether the number of rainy days and the sunshine duration were correlated with the incidence of dengue fever in the city of Yogyakarta. Methodology/Approach – This study uses a retrospective analytic observational method. This study was conducted by analyzing the relationship between monthly data on the number of rainy days and duration of sunshine with cases of dengue fever in the city of Yogyakarta in 2015-2019. Climatic data were obtained from the recording of the Yogyakarta Mlati Climatology Station and data on dengue cases were obtained from the records of the Yogyakarta City Health Office. The data was then analyzed by the Spearman correlation test to find the correlation between the two variables. DHF with an accumulation of 3705 cases during 2015-2019. The city has a tropical climate with an average of 8.96 rainy days and 66% of sunshine duration per month. In the Spearman correlation test, it is found that there was no relationship between DHF cases and the number of rainy days, which had a non-significant positive correlation (p = 0.056 ; r = 0.249) and there was no relationship between DHF cases and sunshine duration had a negative and insignificant correlation (p = 0.316; r = - 0.132). There is no significant relationship between the number of rainy days and the sunshine duration with the incidence of DHF in the city of Yogyakarta. There is a difference in the direction of the correlation between the two variables, namely the number of rainy days is positively correlated while the sunshine duration is negatively correlated with the incidence of DHF in Yogyakarta City. Originality/ Value/ Implication – This study proves that the factor of the number of rainy days shows a positive correlation with the number of cases of DHF, while the factor of the sunshine duration shows a negative correlation in the city of Yogyakarta.

The effect of weather and climate on dengue outbreak risk in Peru, 2000-2018: A time-series analysis.

BackgroundDengue fever is the most common arboviral disease in humans, with an estimated 50-100 million annual infections worldwide. Dengue fever cases have increased substantially in the past four decades, driven largely by anthropogenic factors including climate change. More than half the population of Peru is at risk of dengue infection and due to its geography, Peru is also particularly sensitive to the effects of El Niño Southern Oscillation (ENSO). Determining the effect of ENSO on the risk for dengue outbreaks is of particular public health relevance and may also be applicable to other Aedes-vectored viruses.MethodsWe conducted a time-series analysis at the level of the district-month, using surveillance data collected from January 2000 to September 2018 from all districts with a mean elevation suitable to survival of the mosquito vector (<2,500m), and ENSO and weather data from publicly-available datasets maintained by national and international agencies. We took a Bayesian hierarchical modeling approach to address correlation in space, and B-splines with four knots per year to address correlation in time. We furthermore conducted subgroup analyses by season and natural region.ResultsWe detected a positive and significant effect of temperature (°C, RR 1.14, 95% CI 1.13, 1.15, adjusted for precipitation) and ENSO (ICEN index: RR 1.17, 95% CI 1.15, 1.20; ONI index: RR 1.04, 95% CI 1.02, 1.07) on outbreak risk, but no evidence of a strong effect for precipitation after adjustment for temperature. Both natural region and season were found to be significant effect modifiers of the ENSO-dengue effect, with the effect of ENSO being stronger in the summer and the Selva Alta and Costa regions, compared with winter and Selva Baja and Sierra regions.ConclusionsOur results provide strong evidence that temperature and ENSO have significant effects on dengue outbreaks in Peru, however these results interact with region and season, and are stronger for local ENSO impacts than remote ENSO impacts. These findings support optimization of a dengue early warning system based on local weather and climate monitoring, including where and when to deploy such a system and parameterization of ENSO events, and provide high-precision effect estimates for future climate and dengue modeling efforts.

Fulminant Myocarditis: A Very Rare Manifestation of Dengue Fever

Dengue is a highly prevalent arthropod-borne viral disease in tropical and subtropical areas of the globe. The majority of dengue cases are benign but rare complications and presentations are seen increasingly due to the rising burden of the disease mainly in tropical countries. In dengue, clinical manifestations vary from asymptomatic infection to severe disease. Dengue fever is characterised by fever, myalgia, arthralgia, headache and bleeding manifestations. We report a rare case of dengue fever complicated with acute myocarditis. The patient recovered gradually with supportive care.

The Use of Natural Insecticides in the Control of The Aedes Aegypti Mosquito

One of the problems that are closely related to the community is the case of dengue fever and the use of synthetic insecticides, which cause environmental, insect resistance, and health losses for the community. To reduce the use of synthetic insecticides, this research focuses on the use of natural insecticides in controlling the Aedes Aegypti mosquito. The method in this study is true experiment research using a completely randomized design with 6 treatments 4 repetitions with 1 aqua dest control. Natural insecticides are made from Lemongrass and eco enzymes, then sprayed onto Aedes Aegypti mosquitoes in each cage containing 10 mosquitoes, the total mosquitoes tested were 280 adult mosquitoes. The purpose of this study was to formulate a natural insecticide that is effective in killing the Aedes Aegypti mosquito and to analyze the public's acceptance of the natural insecticide made. The results showed that the 4th treatment, namely 2:1 (citronella: eco enzymes) had the highest killing power with a mortality rate of 92.5% with an average time of killing mosquitoes of 1 minute. More than 50% of the survey of 20 respondents accepted or liked natural insecticides made from aspects of color appearance, ease of use, availability of materials, and the desire to use natural insecticides, while the smell of natural insecticides, people did not accept because the smell was quite strong.

HUBUNGAN SANITASI LINGKUNGAN DAN TINDAKAN 3M PLUS TERHADAP KEJADIAN DBD

&#x0D; From 1968 until 2012 the World Health Organization (WHO) noted the state of Indonesia as a country with cases of dengue fever were the highest in Southeast Asia. In 2015, dengue cases continue to rise in the working area of the health center Kenali Besar, this led some villages in the area of workplace health centers recognize the great including dengue endemic area. Type of research is quantitative research with cross sectional method. Samples taken in this study correspond to proportional random sampling as many as 95 respondents.The results of the analysis of a significant relationship between the clean water reservoirs with the incidence of dengue fever in the region health centers Kenali Besar (p value = 0.006 p≤ 0.05). There is a significant relationship between the provision of private trash with the incidence of dengue fever in the region health centers Kenali Besar (p value = 0.002 p≤ 0.05). There is a significant relationship between the actions of 3M Plus with the incidence of dengue fever in the region health centers Kenali Besar (p value = 0.048 p≤ 0.05).There is a relationship between the water infrastructure, the provision of personal trash and acts 3M Plus the incidence of dengue in the region health centers Kenali Besar Recognize the Great.&#x0D;

Addressing delayed case reporting in infectious disease forecast modeling.

Infectious disease forecasting is of great interest to the public health community and policymakers, since forecasts can provide insight into disease dynamics in the near future and inform interventions. Due to delays in case reporting, however, forecasting models may often underestimate the current and future disease burden.In this paper, we propose a general framework for addressing reporting delay in disease forecasting efforts with the goal of improving forecasts. We propose strategies for leveraging either historical data on case reporting or external internet-based data to estimate the amount of reporting error. We then describe several approaches for adapting general forecasting pipelines to account for under- or over-reporting of cases. We apply these methods to address reporting delay in data on dengue fever cases in Puerto Rico from 1990 to 2009 and to reports of influenza-like illness (ILI) in the United States between 2010 and 2019. Through a simulation study, we compare method performance and evaluate robustness to assumption violations. Our results show that forecasting accuracy and prediction coverage almost always increase when correction methods are implemented to address reporting delay. Some of these methods required knowledge about the reporting error or high quality external data, which may not always be available. Provided alternatives include excluding recently-reported data and performing sensitivity analysis. This work provides intuition and guidance for handling delay in disease case reporting and may serve as a useful resource to inform practical infectious disease forecasting efforts.

Seasonal variations in dengue virus transmission suitability in the Americas

Dengue fever (DF) is associated with significant morbidity across the tropics and sub-tropics. Here, we used a temperature-based model of the extrinsic incubation period (EIP) and a temperature and humidity-based model for adult mosquito survival to explore the relationship between seasonal climate variability and DF in Brazil from 2014 to 2019. We found that municipalities with higher mosquito survival probabilities and shorter EIPs were more likely to be associated with DF case reports, but with significant intra-annual variability. A 0.012 or above probability of Aedes aegypti surviving the EIP was associated with a greater than 50% probability of DF being reported in the municipality. We extrapolated these results to the Americas using climate data over the last decade (2010–2019) to map the seasonal change in the range of areas suitable for dengue virus transmission and the magnitude of the population living in those areas. Areas near the Equator exhibited high suitability throughout the year whereas suitability in the subtropics and temperate regions varied seasonally, especially moving poleward. Strengthening our understanding of DF seasonality is essential to mitigating risks, particularly as the Americas experience the impacts of climate change.

PREVALENCE OF DENGUE HEMORRHAGIC FEVER IN BALI FROM 2015 TO 2020 AND DURING THE COVID-19 PANDEMIC

Background: Dengue hemorrhagic fever cases increased significantly during the COVID-19 pandemic phase. Purpose: This study defines, describes, and evaluates the dengue hemorrhagic fever incidence in Bali Province from 2015 to 2020 and in the context of the COVID-19 pandemic. Methods: The various types of descriptive study with case series design. The study used an environmental epidemiology approach to analyze the health profile of Bali Province. The number of DHF cases in 2015-2020, DHF-related morbidity and death rates, larva-free rates, climate, population and population density, and gender were variables in this study. The study took place in May and June 2021. Results: The prevalence of dengue hemorrhagic fever in the province of Bali fluctuated between 2015 and 2020. The highest number of dengue cases in 2016 was 20,306, and they fell from 2017 to 2019. Cases doubled in 2020, up by 12,173. The endemic areas with the highest prevalence of cases are in the districts of Buleleng and Badung. The highest incidence rate was in 2016 at 483/100,000 population, and for the last five years, it has not met the national target of 49/100,000 population. The highest CFR figure in 2020 was 0.43%, an increase of 1.5 times during the COVID-19 pandemic. Conclusion: The prevalence of dengue hemorrhagic fever cases in Bali in 2015 – 2020 fluctuated significantly, and mortality due to dengue during the COVID-19 pandemic experienced a significant increase.

Chest Pain in a Patient with Dengue Fever Resembling Acute Myocardial Infarction: A Case Report

Dengue is an arthropod-borne viral disease. Dengue fever may present with dengue hemorrhagic fever/dengue shock syndrome. Now a days some atypical and rare manifestations are noticed involving liver, central nervous system and heart. Here we reported a case of dengue fever in 25 years young man having high level of cardiac biomarkers and ECG changes mimicking myocardial infarction initially but later on further evaluation of the case confirmed as acute myocarditis due to dengue fever. JAFMC Bangladesh. Vol 17, No 2 (December) 2021: 99-102

The Effects of Meteorological Factors on Dengue Cases in Malaysia.

Dengue is a vector-borne disease affected by meteorological factors and is commonly recorded from ground stations. Data from ground station have limited spatial representation and accuracy, which can be overcome using satellite-based Earth Observation (EO) recordings instead. EO-based meteorological recordings can help to provide a better understanding of the correlations between meteorological variables and dengue cases. This paper aimed to first validate the satellite-based (EO) data of temperature, wind speed, and rainfall using ground station data. Subsequently, we aimed to determine if the spatially matched EO data correlated with dengue fever cases from 2011 to 2019 in Malaysia. EO data were spatially matched with the data from four ground stations located at states and districts in the central (Selangor, Petaling) and east coast (Kelantan, Kota Baharu) geographical regions of Peninsular Malaysia. Spearman’s rank-order correlation coefficient (ρ) was performed to examine the correlation between EO and ground station data. A cross-correlation analysis with an eight-week lag period was performed to examine the magnitude of correlation between EO data and dengue case across the three time periods (2011–2019, 2015–2019, 2011–2014). The highest correlation between the ground-based stations and corresponding EO data were reported for temperature (mean ρ = 0.779), followed by rainfall (mean ρ = 0.687) and wind speed (mean ρ = 0.639). Overall, positive correlations were observed between weekly dengue cases and rainfall for Selangor and Petaling across all time periods with significant correlations being observed for the period from 2011 to 2019 and 2015 to 2019. In addition, positive significant correlations were also observed between weekly dengue cases and temperature for Kelantan and Kota Baharu across all time periods, while negative significant correlations between weekly dengue cases and temperature were observed in Selangor and Petaling across all time periods. Overall negative correlations were observed between weekly dengue cases and wind speed in all areas from 2011 to 2019 and 2015 to 2019, with significant correlations being observed for the period from 2015 to 2019. EO-derived meteorological variables explained 48.2% of the variation in dengue cases in Selangor. Moderate to strong correlations were observed between meteorological variables recorded from EO data derived from satellites and ground stations, thereby justifying the use of EO data as a viable alternative to ground stations for recording meteorological variables. Both rainfall and temperature were found to be positively correlated with weekly dengue cases; however, wind speed was negatively correlated with dengue cases.

Effects of COVID-19 Non-Pharmacological Interventions on Dengue Infection: A Systematic Review and Meta-Analysis.

Non-pharmacological interventions (NPIs) implemented during the coronavirus disease 2019 (COVID-19) pandemic have demonstrated significant positive effects on other communicable diseases. Nevertheless, the response for dengue fever has been mixed. To illustrate the real implications of NPIs on dengue transmission and to determine the effective measures for preventing and controlling dengue, we performed a systematic review and meta-analysis of the available global data to summarize the effects comprehensively. We searched Embase, PubMed, and Web of Science in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines from December 31, 2019, to March 30, 2022, for studies of NPI efficacy on dengue infection. We obtained the annual reported dengue cases from highly dengue-endemic countries in 2015–2021 from the European Centre for Disease Prevention and Control to determine the actual change in dengue cases in 2020 and 2021, respectively. A random-effects estimate of the pooled odds was generated with the Mantel-Haenszel method. Between-study heterogeneity was assessed using the inconsistency index (I2 ) and subgroup analysis according to country (dengue-endemic or non-endemic) was conducted. This review was registered with PROSPERO (CRD42021291487). A total of 17 articles covering 32 countries or regions were included in the review. Meta-analysis estimated a pooled relative risk of 0.39 (95% CI: 0.28–0.55), and subgroup revealed 0.06 (95% CI: 0.02-0.25) and 0.55 (95% CI: 0.44-0.68) in dengue non-endemic areas and dengue-endemic countries, respectively, in 2020. The majority of highly dengue-endemic countries in Asia and Americas reported 0–100% reductions in dengue cases in 2020 compared to previous years, while some countries (4/20) reported a dramatic increase, resulting in an overall increase of 11%. In contrast, there was an obvious reduction in dengue cases in 2021 in almost all countries (18/20) studied, with an overall 40% reduction rate. The overall effectiveness of NPIs on dengue varied with region and time due to multiple factors, but most countries reported significant reductions. Travel-related interventions demonstrated great effectiveness for reducing imported cases of dengue fever. Internal movement restrictions of constantly varying intensity and range are more likely to mitigate the entire level of dengue transmission by reducing the spread of dengue fever between regions within a country, which is useful for developing a more comprehensive and sustainable strategy for preventing and controlling dengue fever in the future.