Dengue Hemorrhagic Fever Outbreak Research Articles

Evaluation of one-house one-larvae observer program in controlling dengue hemorrhagic fever in Central Sulawesi

Dengue hemorrhagic fever (DHF) is still a health problem in Poso District. This can be seen from the high number of DHF cases and potential outbreaks from 2017 to 2018. The local government took the initiative to prevent DHF outbreaks in Poso Regency. The Central Sulawesi Provincial Health Office and the Poso Regency Health Office have implemented onehouse one-larvae observer program in the Poso Kota Selatan District area by engaging the local government and community. The implementation of the program and its accomplishments requires evaluation. This study aims to evaluate the one-house one-larvae observer program using input, process, output, and outcome indicators. The research adopts a descriptive-qualitative approach, employing observation and interviews within an evaluation research design. Data analysis was performed using interpretation and triangulation methods. Policy documents are available, and human resources supporting the program are in compliance with the decree. However, the budget for the program is insufficient, while the available infrastructure is sufficient. The process indicators demonstrate satisfactory progress. Based on outputs, there was an increase in achievement against the program target of the number of buildings inspected by house larvae observers over four years. The outcome indicator in the form of the larvae-free rate increased by >90% during one year of program implementation. The implementation of local innovations initiated by the Regency Health Office and stakeholders’ engagement has been proven to increase community participation in programs that impact the achievement of program outputs and outcomes.

AN EPIDEMIOLOGICAL OVERVIEW OF DENGUE HEMORRHAGIC FEVER (DHF) CASES IN KEDIRI REGENCY DURING 2017-202

Background: Dengue Hemorrhagic Fever (DHF) is a communicable disease with rapid spread and the potential to cause death. In 2019, Kediri District had the fourth-highest number of DHF cases in East Java Province and was reported to have experienced a DHF outbreak. Objective: This study aimed to describe dengue cases in Kediri District in 2017-2021 under non-pandemic and COVID-19 pandemic conditions. Methods: Using a total sampling technique, descriptive research with a case series design was conducted using secondary data from the Health Profiles and the Central Bureau of Statistics of Kediri District in 2017-2021. The studied variables included the number of dengue cases, sex, age, area, population, population density, morbidity rate, Lateral Flow Immunoassay (LFI), and rainfall. Data were analyzed using an epidemiological approach based on people, places, and times and visualized with tables and diagrams. Results: The majority of DHF cases occurred in males and the 5-14 years age group in both the COVID-19 non-pandemic (52.88%; 55.96%) and COVID-19 pandemic conditions (51.14%; 58.56%). The incidence rate (IR) increased with population density and the number of dengue cases in the non-COVID-19 pandemic. It decreased with a decrease in dengue cases when the population density increased during the COVID-19 pandemic. Under all conditions, high dengue cases were found in months with high rainfall. Conclusion: The pattern of DHF incidence in Kediri District in 2017-2021 is mostly in males and the age group of 5-14 years, when there is an increase in population density, and in January.

Predicting potential areas at risk of the Dengue Hemorrhagic Fever in Jakarta, Indonesia—analyzing the accuracy of predictive hot spot analysis in the absence of small geographical area data

ABSTRACT Dengue Hemorrhagic Fever (DHF), a more severe form of dengue, is one of the most rapidly spreading mosquito-borne diseases in the world. This study is motivated by the rising DHF incidence in Jakarta, the capital city of Indonesia. We mainly utilized hot spot analysis, which employs spatial statistics to find at-risk areas for DHF outbreaks in Jakarta’s five municipalities. However, producing informative results from hot spot analysis requires a complete set of data on each of Jakarta’s 42 districts, which is not available. We thus propose the idea of using small area estimation (SAE) and machine learning to make up for the lack of data. To evaluate whether this proposed method is effective, we compare the hot spot results from the estimation with the actual data of each district. The results show that the estimated hot spot map is similar to the hot spot map from the actual data. This implies that it is possible to find potential at-risk areas of dengue fever without a complete dataset in every small geographic area. We expect that this research can increase the performance of DHF control measures at the district level, even in the absence of small area data.

Integration of climate, transmission, and spread of dengue hemorrhagic fever in endemic areas

Introduction. Dengue Hemorrhagic Fever (DHF) is still a public health problem even in the era of the COVID-19 pandemic in 2020, including in Indonesia. This study aimed to analyze the incidence of DHF based on the integration of climatic factors, including rainfall, humidity, air temperature, and duration of sunlight and their distribution. Materials and Methods. This was an ecological time series study with secondary data from the Surabaya City Health Office covering the incidence of DHF and larva-free rate and climate data on rainfall, humidity, air temperature, and duration of sunlight obtained from the Meteorology and Geophysics Agency (BMKG). Silver station in Surabaya, the distribution of dengue incidence during 2018-2020. Results and Discussion. The results showed that humidity was correlated with the larvae-free rate. Meanwhile, the larva-free rate did not correlate with the number of DHF cases. DHF control is estimated due to the correlation of climatic factors and the incidence of DHF, control of vectors and disease agents, control of transmission media, and exposure to the community. Conclusions. The integration of DHF control can be used for early precautions in the era of the COVID-19 pandemic by controlling DHF early in the period from January to June in Surabaya. It is concluded that humidity can affect the dengue outbreak and it can be used as an early warning system and travel warning regarding the relative risk of DHF outbreak.

Utilization of Animated Films as Digital-based Socialization Media for Prevention of Dengue Hemorrhagic Fever Outbreaks in the Malang City Region during the COVID-19 Pandemic

BACKGROUND: The increase in dengue cases in the coronavirus disease (COVID-19) pandemic is affected by restrictions on human movement, climate, human behavior, and knowledge. Animated film for communication media based on digital technology as a promotional and preventive tool regarding dengue hemorrhagic fever (DHF) in the era of the COVID-19 pandemic. AIM: The purpose of this study is to increase knowledge and attitudes among productive-age youth as part of efforts to prevent DHF cases during the COVID-19 pandemic and in the future. METHODS: A pre-experimental study design with a one-group pre-test and post-test design was used in this study, so only one group was studied. In this study, using total sampling, as many as 30 respondents from the total population who are Grade 1 students at one of the junior high schools in Malang City. RESULTS: The difference test on knowledge produced an asymptotic sig value of 0.000, which is (<0.05). This means that the average post-test score obtained is higher and significantly different from the pre-test. In addition, based on the results of the difference test on attitudes, an Asymp Sig value of 0.001 is obtained, which is (<0.05). This means that the average post-test score obtained is higher and significantly different from the pre-test. CONCLUSION: Animated films as digital-based socialization media can help increase students’ knowledge and attitudes in efforts to prevent DHF outbreaks.

Model Forecasting Development for Dengue Fever Incidence in Surabaya City Using Time Series Analysis

Dengue hemorrhagic fever (DHF) is one of the most widespread and deadly diseases in several parts of Indonesia. An accurate forecast-based model is required to reduce the incidence rate of this disease. Time-series methods such as autoregressive integrated moving average (ARIMA) models are used in epidemiology as statistical tools to study and forecast DHF and other infectious diseases. The present study attempted to forecast the monthly confirmed DHF cases via a time-series approach. The ARIMA, seasonal ARIMA (SARIMA), and long short-term memory (LSTM) models were compared to select the most accurate forecasting method for the deadly disease. The data were obtained from the Surabaya Health Office covering January 2014 to December 2016. The data were partitioned into the training and testing sets. The best forecasting model was selected based on the lowest values of accuracy metrics such as the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). The findings demonstrated that the SARIMA (2,1,1) (1,0,0) model was able to forecast the DHF outbreaks in Surabaya City compared to the ARIMA (2,1,1) and LSTM models. We further forecasted the DHF cases for 12 month horizons starting from January 2017 to December 2017 using the SARIMA (2,1,1) (1,0,0), ARIMA (2,1,1), and LSTM models. The results revealed that the SARIMA (2,1,1) (1,0,0) model outperformed the ARIMA (2,1,1) and LSTM models based on the goodness-of-fit measure. The results showed significant seasonal outbreaks of DHF, particularly from March to September. The highest cases observed in May suggested a significant seasonal correlation between DHF and air temperature. This research is the first attempt to analyze the time-series model for DHF cases in Surabaya City and forecast future outbreaks. The findings could help policymakers and public health specialists develop efficient public health strategies to detect and control the disease, especially in the early phases of outbreaks.

THE RELATIONSHIP OF ENVIRONMENTAL FACTORS AND THE EXISTENCE OF LARGER WITH THE EVENT OF Dengue Hemorrhagic Fever (DHF) IN PASURUAN REGENCY

Dengue Hemorrhagic Fever (DHF) is an acute viral-febrile disease, often characterized by headache, bone or joint pain and muscle, and rash as a symptom. In Indonesia in 2011 there were 65,432 cases with 595 deaths. East Java Province has determined outbreaks of DHF since 2015 in 37 districts / cities, with a total of 3,136 cases of dengue fever and 52 deaths. Pasuruan Regency is one of Kabupeten in East Java with the highest death rate from DHF compared to other regencies or cities, which is 28 people in 2020. There are many factors that can affect, pray the only environment and vector. The purpose of this research is to see the relationship of environmental factors and vector with the incidence of DBD in Pasuruan Regency. This research is an observational research with case control design. The sample in this research were 76 respondents consisting of 38 case groups and 38 control groups representing from 3 sub-districts in Pasuruan Regency (Gempol, Beji and Kraton Sub-district). Data analysis with Chi-Square test. The results showed that there was a relationship between water pH in house (p = 0.005, OR = 5,343), indoor air temperature (p = 0.046, OR = 3,221), air humidity in house (p = 0.049, OR = 3,923) and presence of larvae (p = 0.037, OR = 3.032) with the incidence of DHF in Pasuruan Regency. The most influential factor in increasing the risk of DHF incidence in Pasuruan Regency is the pH of water, the temperature inside the house and the presence of larvae around the house. It needs cross-sector cooperation to pay attention to the condition of environmental sanitation so it will not be a good place for Ae mosquito development. aegypti. Providing counseling to people who focus on the source of the problem, and the community in order to prevent the occurrence of transmission of DHF by breaking the chain of transmission.

The Distribution of Dengue Virus Serotype in Quang Nam Province (Vietnam) during the Outbreak in 2018.

Objectives: Quang Nam province in the Centre of Vietnam has faced an outbreak of dengue hemorrhagic fever (DHF) in 2018. Although DHF is a recurrent disease in this area, no epidemiological and microbiological reports on dengue virus serotypes have been conducted mainly due to lack of facilities for such a kind of advanced surveillance. The aim of this study was to detect different dengue virus serotypes in patients’ blood samples. Design and Methods: Suspected cases living in Quang Nam province (Vietnam) and presenting clinical and hematological signs of dengue hemorrhagic fever were included in the study. The screening was performed, and the results were compared by using two methodologies: RT real-time PCR (RT-rPCR) and the Dengue NS1 rapid test. Results: From December 2018 to February 2019, looking both at RT-rPCR [+] and NS1 [+] methodologies, a total of 488 patients were screened and 336 were positive for dengue virus detection (74 children and 262 adults); 273 of these patients (81.3%) underwent viral serotype identification as follows: 12.82% (35/273) D1 serotype, 17.95% (49/273) D2, 0.37% (1/273) D3, 68.50 (187/283) D4, and 0.37% (1/273) D2+D4 serotypes. The RT-rPCR outcomes showed higher sensitivity during the first three days of infection compared to NS1 (92.3% vs. 89.7%). The NS1 increased sensitivity after the first 3 days whilst the RT-rPCR decreased. Conclusions: Advanced surveillance with dengue virus serotypes identification, if performed routinely, may help to predict and prevent further DHF epidemics based on the exposure of the different serotypes during different periods that lead to the intensification of disease severity as a consequence of antibody-dependent enhancement (ADE).

Pembuatan Obat Nyamuk Herbal Sebagai Alternatif Pembasmi Nyamuk Di Desa Sopu Kabupaten Sigi

Aedes is a genus of mosquitoes that often cause health problems. The genus Aedes is a biological vector of DHF (Dengue Hemorrhagic Fever). Concern over the current outbreak of DHF (Dengue Hemorrhagic Fever) has resulted in the use of many chemical-based insect repellents such as insecticides to eradicate mosquitoes. However, these things can cause toxic residues that are harmful to human and livestock health, environmental pollution and can cause unwanted effects such as natural enemies if used continuously and for a long time. Currently, electric mosquito repellent is one of the people's choices. Therefore, to make people aware of the importance of high selectivity in using mosquito repellent that is safe for health and the environment, it is necessary to have community service regarding and training regarding the use and manufacture of herbal mosquito repellent. Hernal mosquito repellent is made from a mixture of natural ingredients that contain nicotinic substances that can protect us from mosquitoes. The materials used for the manufacture of mosquito repellent are very easy to find or easy to obtain. Because it only uses orange peel and garlic as the basic ingredients. The method of manufacture is also very easy so that it is also easy to apply among housewives. The manufacture of herbal mosquito repellent made from garlic and orange peel is an alternative as an insect repellent that is safe for health in terms of the ingredients

Description of Extraordinary Events of Dengue Hemorrhagic Fever In Belu Regency, East Nusa Tenggara Province 2020

Belu Regency is located in the province of East Nusa Tenggara (NTT), Indonesia and is an endemic area for dengue fever. Nationally, until June 2020, there were 16,320 cases of dengue fever with a CFR of 0.009%, while in Belu Regency there were 820 cases recorded until June 2020 with a CFR of 0.97%. This study aims to describe the outbreak of DHF by person, place and time as well as the distribution of cases in Belu Regency. this research is descriptive observational with case series design. The source of research data is secondary data on dengue cases obtained from the 2016-2019 Dengue Hemorrhagic Fever (DHF) Report and the DHF outbreak report in January-June 2020, the Belu District Health O ce. DHF cases in Belu Regency until June 2020 were 820 cases with symptoms of fever 2-7 days by 100% and supported by laboratory platelet examinations of 73%. The highest IR rate until June 2020 is 367 per 100. 000 residents with a CFR of 0.97% spread over 12 sub-districts of Belu Regency. The highest IRs (>20 per 10,000 population) are Atambua city, South Atambua, East Tasifeto, West Atambua, Kakuluk Mesak and West Tasifeto subdistricts. The majority of DHF in the age group 5-14 years 521 cases (27.1%) with female sex as many as 495 cases (51.51%). DHF cases were found since the first epidemiological week at the beginning of the year with peak cases at the 13th week. Belu Regency Is a dengue endemic area with an IR of 367/100,000 population with a CFR of 0.97%. The highest cases were in the 5-14 year age group and spread across 12 sub-districts of Belu Regency.

Analysis of climatic variability and dengue hemorrhagic fever incidence at the Tsunami Area Banda Aceh City

The rebuilding of post-tsunami community residential an area in Banda Aceh City has created a new ecosystem and at the same time a public health problem. The construction of new settlements has an impact on the emergence of Aedes aegypti habitat. The post-tsunami climate factor is thought to be one of the factors that cause outbreaks of dengue hemorrhagic fever (DHF) cases every year in Banda Aceh City. This study aims to analyze the relationship between climatic variability with the DHF incidence cases from 2010-2020 at the tsunami area Banda Aceh City. The study uses monthly DHF case data obtained from the Banda Aceh City Health Office. Monthly climate data were obtained from the Meteorology, Climatology, and Geophysics Agency of Aceh Province. Spearman’s correlation analysis shows that temperature, humidity, rainfall, and wind velocity have a significant relationship with the DHF incidence cases. Humidity and rainfall are positively correlated with DHF incidence, while temperature and wind velocity shows a negative correlation with DHF incidence. This study shows that climate is one of the factors influential in the DHF incidence cases at the tsunami area Banda Aceh City.

Impact of Climate Change on Dengue Hemorrhagic Fever (DHF) in Tropical Countries: A Literature Review

Introduction: Dengue Hemorrhagic Fever (DHF) is a zoonotic disease that is most wary because the cases reported by WHO increased quite drastically from 2.4 million cases to 5.2 million cases in 2010-2019 globally. In 2020, the DHF rate increased by 953,476, and the majority occurred in tropical countries. In response to this, WHO emphasized that climate and weather variables can play an important role in predicting the DHF outbreak. This article was written to find out the impact of climate change on the incidence of DHF. Discussion: The literature review method was used in writing this article by utilizing article searches in online databases, namely PubMed, DOAJ, Proquest, and Science Direct. Amount 11 articles related to the title have been selected as literacy materials. Climatic variables consisting of temperature, rainfall, and humidity have the potential to increase the incidence of DHF. Conclusion: It can be concluded that climate change indicators can affect the breeding place of the Aedes aegypty, making the various incidence of DHF cases in tropical or subtropical countries. This can be an early warning for each region always to carry out active surveillance in detecting the risk of increasing DHF cases in certain weather.

Temporal and spatial characteristics of the dengue hemorrhagic fever outbreak in Hanoi in 2017

Dengue hemorrhagic fever/dengue fever is a mosquito-borne viral disease that has re-emerged in recent years. In 2017, the largest recorded outbreak of dengue appeared in Hanoi, Vietnam, with over 37,000 cases and seven deaths. This study aimed to describe the temporal and spatial characteristics of the dengue hemorrhagic fever outbreak in Hanoi in 2017. We used heat maps, hotspot and cold spot, and cluster analysis to describe and analyze the development of the outbreak of dengue hemorrhagic fever in all 30 districts of the city of Hanoi. The results show that in 2017, Hanoi experienced the most serious dengue outbreak since 1992 with 37,665 cases recorded including seven deaths (CFR: 0.02%), or 492 cases per 100,000 persons, which makes dengue a serious public health threat in Hanoi. The outbreak not only produced a very large number of cases, but also expanded by space, with 25 districts having an incidence greater than 100 cases per 100,000 persons. The highest incidences were still concentrated in the urban and suburban areas. Dengue hemorrhagic fever is currently a serious public health issue in Hanoi, which needs attention especially for prevention.

The Early Vigilance of Dengue Hemorrhagic Fever Outbreak in the Community

Early Awareness of Extraordinary Events of Dengue Hemorrhagic Fever (DHF) was asked to community (n= 130). Precautions were measured based on community knowledge, attitudes, and behavior. Knowledge, attitude, and behavior are constructs (in the form of a composite variable) from an early awareness of DHF outbreak. The result showed that the knowledge related to the transmission factor and the proliferation of dengue disease was quite good (72.3%). The DHF risk control was also good (93.9%) while the dengue fever eradication was still poor (67.7%). However, the attitude showed that it is still not ready to act on the basis of consciousness. Meanwhile, the results of the data analysis identified that the model of the early awareness measurement on DHF outbreak which consisted of construct variables (knowledge, attitude, and action) were a perfect fit. Based on the measurement model, the level of community awareness on DHF disease can be measured. This showed that the level of early awareness of DHF disease was good 76.2% and only 3.8% were less alert. This means although the less alert percentage is quite small, if people have an attitude of indifference to the prevention of DHF then the impact will affect a wider community.

Comparation of Elman neural network, long short-term memory, and gated recurrent unit in predicting dengue hemorrhagic fever at DKI Jakarta

Dengue hemorrhagic fever (DHF) is a seasonal disease that has quickly spread throughout the world in the past few years. It is caused by the dengue virus that is transmitted by a biological vector in the form of mosquitoes. In DKI Jakarta, the capital of Indonesia, there were 970 DHF cases at the beginning of 2020, thus placing Jakarta in the red zone for the spread of DHF. Besides, DHF can emerge due to various weather and climate factors such as humidity, rainfall, and temperature. With a significant increase in the number of potentially fatal DHF cases in DKI Jakarta, preventing DHF outbreaks is recommended. This research aims to predict the number of DHF cases in DKI Jakarta using weather and DHF case data. Three machine learning models were employed to predict DHF case numbers: Elman neural network (ENN), long short-term memory (LSTM), and gated recurrent unit (GRU). ENNs have a simplified recurrent neural network (RNN) structure, LSTM is a modified RNN with long-range memory and an activation function for deciding which information should be retained or discarded, and GRUs are modified RNNs that are slightly simpler than LSTMs. These methods were implemented in three different data sets as follows: one with 90% training data and 10% testing data, another with 80% training data and 20% testing data, and finally, one with 70% training data and 30% testing data. A grid search is used to determine the best hyperparameter from all three methods. This will determine the best model for predicting the number of DHF cases in DKI Jakarta (excluding Kepulauan Seribu Regency) according to the data used, RMSE values, and the simulation results. Based on these criteria, LSTM is better suited to predicting the number of DHF cases than ENN or GRU in almost every district in DKI Jakarta.

Spatial analysis of dengue hemorrhagic fever in Talaud Islands regency

Background: The number of dengue hemorrhagic fever (DHF) cases in Indonesia from January to February 2016 was 8,487 with 108 deaths. DHF is an infectious disease that continues to increase from 2014 until 2016 in Manado city. DHF cases in Talaud Islands Regency from 2014 to 2016 were 143 cases. Regional spatial analysis would simplify the distribution of DHF cases in high-risk areas. To be aware of the DHF outbreak cycle, it is necessary to model spatial risk factors based on geographic information systems (GIS) to tackle and eradicate DHF cases by region.Methods: This study aimed to analyze the spread of DHF in Talaud regency based on age, sex, population density and area height. The design of this research is qualitative analytic by using an ecological study approach. The research scope was 19 districts in Talaud regency. Secondary data are used which consists of case number, age, sex, population density, and area height taken from the Talaud district health office with 66 DHF cases in 2018-2019 and analyzed using the GIS approach through spatial analysis.Results: Based on the number of DHF cases that is most in the age group of 5-11 years. Male gender is more likely to suffer from DHF than female. Spatial description of the condition of the altitude in the Talaud Islands regency at risk of suffering from DHF is>50 meters above sea level. Spatial description of population density with most DHF cases is not densely populated area with less than 1,620 inhabitants per km.Conclusions: The health office of Talaud islands regency needs to actively promote health by providing information about eradicating mosquitoes.

The Spatio-Temporal Pattern of Dengue Haemorrhagic Fever, Khon Kaen Province, Thailand During 2008 – 2017

Background: Dengue haemorrhagic fever (DHF) is a major problem in public health of the world and in tropical area especially Africa and South-East Asia. An endemic area of DHF in Thailand has begun since DHF in Khon Kaen province increased and transmitted into all areas. This study examined the spatio temporal pattern of DHF incidence in Khon Kaen during 2008-2017. Method: DHF data were obtained from Bereau of Vector Borne Disease, Khon Kaen province during 2008 – 2017 were geo-code at sub-district level. The data were acquired a space-time with elevated proportions of DHF incidence rate. The spatio-temporal technique analysis were conducted for a DHF transmission. Result: The DHF outbreak in Khon Kaen province, Thailand were decrease in every year but DHF was shifted from urban areas to rural areas. The spatial clustering analysis were identified the risk areas in the district that closed Nakhon Ratchasima province and shifted to Udon Thani province in 2015. Conclusion: The DHF clustered map is one of the best measurement for identified a risk area for surveillance. It has been an effectiveness prevention and controlling plan and allocated a resources of DHF.

CORONAVIRUS DISEASE 2019, DENGUE HEMORRHAGIC FEVER, AND THE CLINICAL SIMILARITY

Recently, coronavirus disease-19 (COVID-19) case is increasing in Indonesia, simultaneously with the outbreak of dengue hemorrhagic fever (DHF). DHF is generally observed to rise at the beginning of the year that peaks between March and April due to the rainy season and high temperatures. The outbreak of COVID-19 started in Wuhan, China, since December 2019, and it has spread quickly worldwide as a pandemic. COVID-19 and DHF have had comparable clinical indication, laboratory highlights, and it has serious implications for the patients as well as for the general health. Therefore, to distinguish, all the doctors in the primary health care have to be aware and to work carefully.

Weekly Forecasting Model for Dengue Hemorrhagic Fever Outbreak in Thailand

Weekly Forecasting Model for Dengue Hemorrhagic Fever Outbreak in Thailand

Investigating dengue outbreak in Tamil Nadu, India

<p><span>Dengue has been indigenous to India in last decade. There was a major outbreak in the state of Tamil Nadu in 2017. Here, we investigate the dengue outbreak in parts of Tamil Nadu, India. Dengue case data were obtained from the hospital records in the Chennai district of Tamil Nadu. The data were analyzed using statistical approaches such as correlation and regression. The result shows that the dengue outbreak in Tamil Nadu during 2017 was due to the population, water stagnation, and sewage, whereas the human activity weren’t the cause of the dengue outbreak which caused 65 deaths. Male constitutes 54.71% whereas female accounted for 45.29% of dengue incidence in Tamil Nadu, majority deaths were children aged less than 10 years due to the outbreak of Dengue Hemorrhagic Fever (DHF). This investigation was evaluated using mathematical regressions, Geographically Weighted Regression (GWR) regression outperformed Ordinary Least Square (OLS) regression model in detecting dengue incidence. This investigation can be strengthened by implementing a surveillance system in parts of Tamil Nadu before an outbreak.</span></p>