Dengue Hemorrhagic Fever Cases Research Articles

Factors Affecting Cases of Dengue Hemorrhagic Fever in Riau Province

One infectious disease that has a high morbidity and mortality rate is Dengue Hemorrhagic Fever. Dengue Hemorrhagic Fever (DHF) is a disease caused by the dengue virus transmitted through the bite of the Aedes aegypti mosquito. In general, the habitat of Aedes mosquitoes is in areas with tropical climates, high rainfall, and hot and humid temperatures. The number of patients and the area of distribution are increasing along with increasing mobility and population density. Improper sanitation can also be a cause of DHF. In Riau province, dengue cases in 2022 continue to increase compared to 2021, with the most cases in Pekanbaru City. This study was conducted to see the factors that influence dengue cases in Riau Province. Using multiple linear regression can measure what factors affect the number of dengue cases. From the results, it was found that population density and sanitation had a significant effect on dengue cases in Riau Province. And judging from the coefficient of determination, it can be interpreted that the variables of population density (X1) and sanitation (X2) simultaneously affect the variable of dengue cases (Y) by 77.8%. While the remaining 22.2% was influenced by other variables that were not studied in this study

Climate Change and Its Impact on the Increase in Dengue Hemorrhagic Fever Cases in North Maluku Province (Case Study in Tidore Islands City)

North Maluku Province has experienced a significant increase in dengue fever cases over the past few years. The purpose of this study is to comprehensively investigate the intricate relationship between climate change and the surge in dengue fever cases in North Maluku Province. This research uses a qualitative case study approach to examine the impact of climate change on dengue fever cases in North Maluku Province. Data was analyzed through in-depth interviews with health workers, local communities, and related stakeholders using NVivo. This robust qualitative data analysis software facilitated the systematic coding, categorization, and thematic exploration of the rich insights gathered during the interviews. The findings show that climate change in this region has significantly impacted the ecology of disease vectors, rainfall patterns, and the spread and prevalence of the Aedes aegypti mosquito as the primary vector of dengue fever. Social, economic, and infrastructure factors also play an essential role in the increase in dengue fever cases. This research provides an in-depth understanding of the relationship between climate change and increased dengue fever cases in North Maluku Province. The implications of these findings underscore the urgency of implementing adaptation and mitigation strategies to address public health risks associated with climate change. This study shows climate change has increased dengue fever cases in North Maluku Province. Therefore, more effective preventive measures, coordination between institutions, and more active community participation are needed to deal with the health impacts caused by climate change.

Dengue Hemorrhagic Fever in North Minahasa Regency in 2021-2022: Study Epidemiological

Dengue Hemorrhagic Fever (DHF) is a disease that rapidly spreads, particularly in tropical and subtropical regions. One of the places affected by DHF cases is North Minahasa Regency, which is one of the top donors to cases in North Sulawesi Province. The purpose of this study is to describe the prevalence of DHF in North Minahasa Regency between 2021 and 2022 in terms of time, place, and person. This is a quantitative descriptive study. This study employed secondary data. This data was collected from the North Minahasa Regency Health Office. Data will be collected from July to October 2023. The data collected were examined univariately. The data showed that the most DHF cases occurred in 2022, with an increase in incidence in March and November. Furthermore, DHF cases were prevalent in Dimembe District (working area of Tatelu Health Center), Kauditan District (working area of Kauditan Health Center), Talawaan District (working area of Talawaan Health Center), Airmadidi District (working area of Airmadidi Health Center), and Kalawat District (working area of Puskesmas Kolongan). The prevalence of DHF cases in 2021-2022 was higher in men, with a total of 150 cases and an average of 76 instances. DHF incidences increased in 2021, particularly in February, August, and December. It can be determined that the largest frequency of DHF in North Minahasa Regency in 2021-2022 occurs between February-March and November-December, were identified in Dimembe District, and the majority of the DHF cases are male

THE RELATION BETWEEN THE NEUTROFIL LYMPHOCYTE RATIO (NLR) AND THE DEGREE OF DENGUE HEMORRHAGIC FEVER IN THE INPATIENT INSTALLATION OF ARI CANTI HOSPITAL FOR THE PERIOD OF APRIL 2022 – MAY 2023

Dengue Hemorrhagic Fever is caused by dengue virus infection which can cause death and cause an outbreak. Neutrophil lymphocyte ratio (NLR) is one of the cheap laboratory parameters and can predict plasma leakage in the critical period of dengue hemorrhagic fever. This study aims to determine the profile of dengue hemorrhagic fever patients and the relationship between the neutrophil lymphocyte ratio and the degree of dengue hemorrhagic fever in patients treated at Ari Canti Hospital for the period April 2022 – May 2023. This research is a retrospective analytical study with a cross-sectional approach using secondary data from archives at the Ari Canti Hospital Inpatient Installation for the period April 2022-May 2023. Data collection in the form of gender, age, neutrophil lymphocyte ratio and degree of dengue hemorrhagic fever was carried out using the convenient purposive sampling method. This study shows that the highest age group is the 26-35-year age group 35.7%, the highest gender is male 55.3% with cases of dengue hemorrhagic fever without shock 89.2% and a neutrophil lymphocyte ratio (NLR) of >2 as much as 64.2%. The result of Mann Whitney non-parametric test, showed that p value <0.0001. There is a significant relationship between NLR and the degree of dengue hemorrhagic fever in patients hospitalized at Ari Canti Hospital in April 2022, May 2023.
 Keywords : dengue virus., dengue hemorrhagic fever., hospitalization., neutrophil lymphocyte ratio

Epidemiological Determinants and Trend Analysis of Dengue Fever Disease

Bandung City is an endemic area for dengue fever, with 4,424 cases and 14 deaths. This research aims to analyze the epidemiological determinants and see the trend analysis to forecast dengue hemorrhagic fever cases. This research used a case-control design. The case population was those who suffered from dengue hemorrhagic fever, while the control population was those who did not suffer from dengue hemorrhagic fever. A sample of 510 respondents was taken. Sampling using a purposive sampling technique. Epidemiological determinants were analyzed using the chi-square test and logistic regression, while disease trends used exponential smooth analysis. The related results were education (p=0.036), presence of mosquito larvae (p=0.000), container material (p=0.002), water container (p=0.025), mosquito wire (p=0.010), presence of solid waste (p=0.002), mosquito repellent plants (p=0.041), mobility (p=0.004). The most dominant epidemiological determinant was the presence of mosquito larvae (OR=3.2). The incidence trend of dengue fever is increasing over the next 5 years. The research concluded that the epidemiological determinants of dengue fever were education, the presence of mosquito larvae, container materials, water collection objects, mosquito wires, the presence of solid waste, and mosquito repellent plants. The presence of mosquito larvae was the dominant factor. There is an increase in dengue fever cases over the next 5 years. It is recommended to increase the larva-free rate by optimizing Jumantik cadres and conducting epidemiological surveillance.

PENERAPAN METODE RUNGE-KUTTA ORDE 4 MODEL PENYEBARAN DEMAM BERDARAH DENGUE DI KOTA MAKASSAR

This research was conducted based on the increasing rate of spread of dengue hemorrhagic fever in the city of Makassar. The aim of this research is to obtain a model for the spread of dengue hemorrhagic fever and find out the numerical solution of the mathematical model. The method used in this research is a quantitative method. The data is processed in the form of quantitative data in the form of the number of people infected, dead and recovered from dengue fever in the city of Makassar in 2021. This research is to predict future dengue hemorrhagic fever cases using the Runge-Kutta Order 4 method. The mathematical model for dengue hemorrhagic fever is in the form of a system of differential equations that includes the variables Sh (Susceptible Host), Ih(Infected Host), Rh (Recovered Host), Sv (Susceptible Vector), dan Iv (Infected Vector). Then look for the parameters that will be used. The research results obtained in january 2022 with Dt = 0,01 using the Fourth Order Runge-Kutta Method with initial values of Sh0= 1426454, Ih0 = 583, Rh0 = 582, Sv0 = 13165, Iv0 = 1215 is Sh100 = 1420142, Ih100 = 2949, Rh100 = 4529, Sv100 = 13706, Iv100 = 751.

Hubungan Perilaku Pencegahan 3M Plus Dengan Kejadian Demam Berdarah Dengue (DBD) Di Wilayah Kerja Puskesmas Bintuhan Kabupaten Kaur

Data from the World Health Organization (WHO) says that in 2022, every year it is estimated that 50-100 million cases of dengue hemorrhagic fever (DHF) will occur in the world. The highest number of DHF in Kaur Regency is in the Bintuhan Community Health Center working area, namely 21 cases in 2022. This research aimed to determine the relationship between 3M Plus prevention behavior and DHF incidents in the Bintuhan Community Health center working area, Kaur Regency. This type of research was Analytical Survey, with a Case Control research design. The case population was all heads of families who had family members suffering from DHF in the period January 2022-April 2023 in the Bintuhan Community Health Center working area, Kaur Regency, totaling 33 families. The control population was all families whose family members did not suffer from DHF in the Bintuhan Community Health Center working area in the period January 2022-April 2023, totaling 3,525 families. The number of samples in this study was 66 heads of families consisting of 33 case samples and 33 control samples, with a ratio of 1:1. The data analysis used in this research was univariate analysis, bivariate analysis using the Chi-Square test. The research results showed that of the 66 heads of families, 39 heads of families (59.1%) implemented 3M Plus prevention behavior and 33 heads of families (50.0%) experienced DHF. There was a relationship between 3M plus prevention behavior and the incidence of DHF in the strong relationship category and odd ratio (OR) = 48,438. It is recommended that the Bintuhan Community Health Center, Kaur Regency, develop strategies for preventing and controlling DHF, one of which is holding aducation about DHF.

Dengue Hemorrhagic Fever in Jepara, Indonesia: Ecological and spatial study based on Environment Parameters

Kedung Village in Jepara Regency stands as one of the areas with the 3rd highest Incidence Rate of Dengue Hemorrhagic Fever (DHF). Contributing factors to the surge in DHF cases include physical environment factors, population density, and vector breeding sites. Despite persistent efforts to control and prevent dengue cases, these endeavors have proven ineffective. The study aimed to comprehensively analyze the physical environment and distribution of DHF cases in Jepara District, Indonesia. This descriptive observational research, focusing on an ecological study, examined a sample of 38 cases in 2020 from one village. The analysis revealed crucial findings: the average temperature ranged from 27-29°C, humidity ranged from 76-88%, and the highest rainfall intensity was 1,301 mm, with the peak occurring in February. The distribution pattern of DHF cases was notably random, with an average distance of 442.63 meters. Moreover, a staggering 92.9% of areas did not meet the Larvafree Index standard, indicating a high risk of transmitting dengue disease, as the House Index (HI) exceeded 5%. Temperature, rainfall, and humidity demonstrated significant correlations with DHF cases in Kedung Village, while no correlation was found between HI and DHF cases

To investigate the relationship between the ABO blood group description and the cases of dengue hemorrhagic fever

To investigate the relationship between the ABO blood group description and the cases of dengue hemorrhagic fever

Performance of CART Time-Based Feature Expansion in Dengue Classification Index Rate

This study proposes utilizing the machine learning technique CART to classify the spread of dengue hemorrhagic fever (DHF). To expand the features used, the CART classification model was developed based on data collected over the previous 2 to 4 years. The data sources included the Bandung City Health Office for the cases of DHF, the Bandung Meteorology, Climatology and Geophysics Agency for the climate data, the Bandung City Central Statistics Agency for population and educational history data. The top-performing CART classification model over the past 2, 3, and 4 years achieved accuracies of 93%, 93%, and 90%, respectively. The models that exhibited the highest accuracy values and optimal number of feature extensions were chosen as the best ones. CART is among several machine learning techniques that can effectively measure the most impactful features during the classification process. The meteorological parameters were found to be irrelevant in the classification process. This study reveals that the population size, male population proportion, and educational attainment levels are the most impactful features in the classification of DHF spread in Bandung City. The research provides valuable insights into the classification of DHF spread in Bandung City through feature expansion.

A study on spatial distribution of infectious diseases based on a normal Q-Q plot and GIS

Background: Distribution of infectiousdisease location based on Geographic Information System (GIS) is considered as an infrastructure in the field of health in formation managment and also known as a fundamental issue in the field of new tachnologies in police medicine. The aim of this article is to carry out a study on spatial distribution of infectious diseases based on a normal Q-Q plot and GIS. Case studies from hand, foot, mouth diseases (HFMD) and dengue hemorrhagic fever (DHF) will be illustrated in Ho Chi Minh city (Vietnam). Methods: The normal Q-Q plot was firstly constructed to study the distribution of HFMD and DHF cases and HFMD and DHF incidence. A GIS was then employed to map the spatial distribution of the HFMD and DHF incidence. Finally, the study results in Ho Chi Minh city was discussed and concluded. Results: It was found that (i) the observed values from HFMD/DHF cases were mostly not on the expected straight line of the normal distribution in the normal Q-Q plot (ii) The high HFMD/DHF infection rate were mainly concentrated in the center of the city. The highest infection rate area was found in District 1, followed by districts District 5, District 3, District 11 and District 11. Whereas, districts having low HFMD/DHF infection rates included District 9, Nha Be, Cu Chi and Can Gio. Conclusions: Findings in this study indicated that the combination of a normal Q-Q plot and a GIS is an effective tool to monitor and control the various infectious diseases.

The relationship of complete blood count on the outcome of childhood patients with Dengue Shock Syndrome (DSS) in the Pediatric Intensive Care Unit (PICU) Dr. Soetomo General Hospital

Dengue Hemorrhagic Fever (DHF) is an acute infectious disease caused by the dengue virus which is spread through the bite of female mosquitoes of the Aedes Aegypti and Aedes Albopictus species. DHF cases often attack children under 15 years of age and if not treated properly it will turn into Dengue Shock Syndrome (DSS). Supporting examinations are needed to diagnose and monitor the condition of DSS patients, one of which is a complete blood test. This study aims to determine the relationship between a complete blood profile and the parameters: platelet count, leukocyte count, hematocrit value, and hemoglobin level on the outcome of pediatric patients with DSS in the Pediatric Intensive Care Unit (PICU) at the Regional General Hospital (RSUD) Dr. Soetomo. This research is a descriptive analytical observational study with a cross sectional approach using medical record data from pediatric patients with DSS in the PICU of Dr. RSUD. Soetomo Surabaya for the 2015-2022 period. The sample consisted of 40 samples in accordance with the inclusion and exclusion criteria taken using total sampling technique. In this study, a significant relationship was found between age, hemoglobin and leukocytes and the mortality outcome of pediatric DSS patients. The values obtained were <0.05 (age), 0.048 (hemoglobin), and 0.048 (leukocytes). Apart from that, there is also a significant relationship between platelets and the outcome of treatment duration for pediatric DSS patients.

PEMODELAN JUMLAH KASUS DEMAM BERDARAH DENGUE DENGAN MENGGUNAKAN MODEL AUTOREGRESSIVE DISTRIBUTED LAG

This study aims to model dengue hemorrhagic fever (DHF) cases with an autoregressive distributed lag (ARDL) model to investigate significant predictor variables in Bojonegoro Regency. The selected predictor variables are the percentage of poverty, population, health facilities, and health workers. A research design with a quantitative approach was used to investigate the predictor variables in dengue cases with the ARDL model and the help of EViews. Stationarity, cointegration, classical assumptions, parameter significance, and model goodness assessment, namely R-square, MSE, AIC, and SBC, were tested. The research data source is secondary data, namely annual data from the reports of the Central Bureau of Statistics and the Health Office in Bojonegoro Regency from 2008 to 2022. The test results show only cointegration in the response variable, so the ARDL model is applied, but the lag distribution is only done on the response variable. In testing the significance of the parameters, it was found that an increase in the health workforce significantly affected the decrease in the number of DHF patients. At the same time, the other predictor variables were not significant

A Comprehensive Economic Analysis of Hospitalised Patients with Dengue Fever

DHF poses a significant public health concern in regions characterised by tropical and subtropical climates. Indonesia is among the nations that have encountered challenges in effectively addressing the issue of DHF, as seen by the escalating number of cases. West Java Province is positioned at the forefront among the top three provinces in terms of reporting the highest number of DHF cases, with a total of 10,722 cases. The number of DHF cases in Depok City shown a notable rise, escalating from 1,276 cases and resulting in 3 fatalities in the year 2020 to a total of 3,155 cases in the subsequent year of 2021. The primary aim of this study was to ascertain the demographic characteristics of families with inpatients and intensive care patients, and to assess the overall financial burden associated with treatment, non-treatment expenses, indirect costs, and economic losses experienced by families of inpatients and intensive care patients afflicted with DHF disease at Depok City Hospital. The present study employed a descriptive analytic strategy utilising a quantitative methodology. The study was carried out at the Depok City General Hospital, utilising both primary and secondary data sources. The population under investigation in this study had a total of 429 patients. The sample size for the study was determined to be 203 using Lameshow's sample size technique. The variables considered in this study encompassed demographic characteristics, the overall direct expenses associated with treatment, the entire direct costs associated with non-treatment, the aggregate indirect costs, and the complete economic losses experienced by families of patients with DHF at Depok City General Hospital. The data underwent analysed through the application of univariate analysis and cost evaluation computation. The findings indicated that the average direct cost of therapy was Rp. 7,797,833 or USD 507.23. The average non-treatment direct expenditures amount to Rp. 2,701,440 or USD 178.59. The average value of indirect costs was Rp. 2,471,557 or USD 163.40. The average family economic loss was Rp. 12,970,830 or USD 843.72. Conclusions: This study demonstrates that the sickness known as dengue hemorrhagic fever (DHF) can result in financial burdens for families, particularly in terms of non-medical direct costs and indirect costs.

MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS

Research on innovations in the statistics and statistical computing program systems implemented in the health sector. The development of a mixed estimator model is an innovation of nonparametric regression analysis by combining two approaches in nonparametric regression, namely the truncated spline estimator and the Epanechnikov kernel. The urgency of this study is that there are often cases where there are different data patterns from each predictor variable. In addition, by using only one form of the estimator in estimating a multivariable regression curve, the result is that the estimator obtained will not match the data pattern. The research objective was to find a mixed estimator between the truncated spline and the Epanechnikov kernel and the estimator results were applied to Dengue Hemorrhagic Fever case data. The unit of observation is a province in Indonesia and This study relied on secondary data received from the Central Statistical Agency (BPS) and the Health Office. Based on the analysis results, it was found that the best model of nonparametric regression with a mixed estimator of the truncated spline and Epanechnikov Kernel is a model with 3 knots with a combination of variables. The coefficient of determination (R2) is 98.11%. We can conclude that the mixed estimator tends to follow actual data and represents a nonparametric regression model with a mixed estimator that can predict the number of Dengue Hemorrhagic Fever Cases in Indonesia

Spatial Analysis on the Spread of Dengue Hemorrhagic Fever in Baubau, Southeast Sulawesi, Indonesia

We studied the spatial patterns of Dengue Hemorrhagic Fever (DHF) transmission in Baubau, a city in Southeast Sulawesi, Indonesia. DHF is a serious disease caused by the dengue virus and spread by Aedes mosquitoes. We used Moran’s Index, a spatial analysis tool, to create a DHF spread map for Baubau’s sub-districts. We found different patterns of DHF risk, such as: cold spots, Betoambari and Batupoaro had lower DHF cases, but they were vulnerable to infection from nearby areas; hot spot, Murhum had higher DHF cases and could transmit the disease to neighboring areas; and low risk, Bungi had the lowest DHF risk and was resilient to infection. Our findings suggest that preventive measures should be tailored to the specific risk level of each sub-district. Our study also provides useful guidance for controlling DHF transmission in Baubau and beyond. Our research is a beacon of hope for a safer and healthier future.

An Assessment of the Relationship Between Population Density and the Incidence of Dengue Hemorrhagic Fever

Background: Dengue is a leading cause of severe illness and hospitalization in Vietnam. This study aims to assess the relationship between population density and dengue hemorrhagic fever (DHF) in August 2023 in Ho Chi Minh city, Vietnam. Methods: Exploratory data analysis (EDA) techniques were first applied to investigate the distribution patterns of DHF incidence. It will go on to use Getis Ord statistic to detect hotspots and coldspots of DHF infection rates. A scatter plot will be then employed to quantitatively assess the relationship between population density and DHF infection rates and Getis Ord statistic. Finally, a dataset of DHF cases reported in August 2023 in Ho Chi Minh city was used to illustrate the proposed methods. Results: It was found that high values of Getis Ord coefficients was mainly concentrated in the east and west of the city. There was a negative correlation between population density and both variables (DHF infection rates and Getis Ord statistic). The population density likely decreases dengue hemorrhagic fever infection rates in August in Ho Chi Minh city. Conclusions: It can be concluded that spatial statistics and EDA have proved their effectiveness in the assessment of the relationship between population density and the incidence of dengue hemorrhagic fever. Findings of this study provide an insight into the effects of population density on DHF infection rates. Keywords: Relationship assessment, Population density, Spatial autocorrelation analysis, Dengue hemorrhagic fever, Infection rate, Ho Chi Minh city.

Analysis of the Distribution Pattern Environmental Risk Factors with the Incidence Dengue Hemorrhagic Fever in South Binjai District, Binjai City

<div><table cellspacing="0" cellpadding="0" align="left"><tbody><tr><td align="left" valign="top"><p class="Default"><em>Environmental conditions have a big influence on the incidence of dengue hemorrhagic fever, because a bad environment can increase the breeding and reproduction of the Aedes aegypti mosquito. Research Objectives: To determine environmental risk factors and distribution patterns of dengue hemorrhagic fever in South Binjai District, Binjai City. The type of research used was analytical observational research with a cross sectional design and an ecological approach. The population in this study was 54.422 people and a sample of 100 people. Analysis of research data with bivariate using Chi square test. And mapping analysis of the distribution of cases of Dengue Hemorrhagic Fever using the Geographic Information System application to describe the distribution pattern of Dengue Hemorrhagic Fever in Binjai City. The results of the study showed that there was a relationship between the presence of larvae and cases of dengue hemorrhagic fever (p-value=0.000), there was a significant relationship between the presence of larvae and cases of dengue hemorrhagic fever (p-value=0.000), there was a significant relationship between the habit of hanging clothes with cases of dengue hemorrhagic fever (p-value=0.000), there is a significant relationship between the frequency of draining the bathtub and cases of dengue hemorrhagic fever (p-value=0.004), there is no significant relationship between the frequency of support from health workers and cases of dengue hemorrhagic fever (p-value = 0.359), and there is no significant relationship between the frequency of experience of receiving health education and cases of dengue hemorrhagic fever (p-value = 0.359). The distribution of dengue fever cases is not spread throughout the sub-district, but only in several adjacent areas. Based on research results, the highest number of cases occurred in mixed plantation areas. It is recommended that health workers compile a more specific distribution pattern map regarding the factors causing Dengue Hemorrhagic Fever.</em></p></td></tr></tbody></table></div><strong><em>Keywords: Dengue hemorrhagic fever, Distribution pattern, Environmental, Risk factors</em></strong>

Spatial model of Dengue Hemorrhagic Fever (DHF) risk: scoping review

BackgroundCreating a spatial model of dengue fever risk is challenging duet to many interrelated factors that could affect dengue. Therefore, it is crucial to understand how these critical factors interact and to create reliable predictive models that can be used to mitigate and control the spread of dengue.MethodsThis scoping review aims to provide a comprehensive overview of the important predictors, and spatial modelling tools capable of producing Dengue Haemorrhagic Fever (DHF) risk maps. We conducted a methodical exploration utilizing diverse sources, i.e., PubMed, Scopus, Science Direct, and Google Scholar. The following data were extracted from articles published between January 2011 to August 2022: country, region, administrative level, type of scale, spatial model, dengue data use, and categories of predictors. Applying the eligibility criteria, 45 out of 1,349 articles were selected.ResultsA variety of models and techniques were used to identify DHF risk areas with an arrangement of various multiple-criteria decision-making, statistical, and machine learning technique. We found that there was no pattern of predictor use associated with particular approaches. Instead, a wide range of predictors was used to create the DHF risk maps. These predictors may include climatology factors (e.g., temperature, rainfall, humidity), epidemiological factors (population, demographics, socio-economic, previous DHF cases), environmental factors (land-use, elevation), and relevant factors.ConclusionsDHF risk spatial models are useful tools for detecting high-risk locations and driving proactive public health initiatives. Relying on geographical and environmental elements, these models ignored the impact of human behaviour and social dynamics. To improve the prediction accuracy, there is a need for a more comprehensive approach to understand DHF transmission dynamics.

Penyuluhan Pentingnya Vaksinasi Covid 19, Pelatihan Pencegahan Deman Berdarah Dengue dan Edukasi kesehatan Gigi untuk Kader Kesehatan Kecamatan Palmerah, Jakarta Barat

In November 2021, Covid-19 vaccination coverage in the special capital area (DKI) Jakarta stage 1 (one) reached 78.1% and stage 2 (two) 60.4% for local identity cards (KTP) DKI Jakarta. Covid-19 vaccination coverage for area the Palmerah District stage 1 (one) has reached 96.56% but unfortunately for stage 2 (two) it has not met the expected target. In order to reduce the Covid-19 case, the regional administration (Pemda) of DKI Jakarta has continued given education and socialization to increase public awareness in implementing health protocols and providing Covid-19 vaccinations to the public.Another problem that occurs in the Palmerah District is the increase cases of Dengue Hemorrhagic Fever (DHF). This increase is due to the rainy season which is the breeding time for the Aedes Aegepty mosquito. DHF can be prevented through controlling the Mosquito Nest Eradication (PSN) programme. Public awareness for healthy behavior and maintaining a mosquito-free home environment is still lacking therefor counseling and training are needed for the community to prevent dengue.Since the Covid 19 pandemic, the Dental Health Education Program could not be implemented in Palmerah Health Center due to pandemic and limited resources. Providing dental health education (DHE) to health cadres will increase oral health in community. The results obtained after the training significantly increased the knowledge of the cadres and community members who participated in the event. Thus this collaboration program should continue regularly to maintain knowledge and health practice in community.