scholarly journals Prospective forecasts of annual dengue hemorrhagic fever incidence in Thailand, 2010–2014

2018 ◽  
Vol 115 (10) ◽  
pp. E2175-E2182 ◽  
Author(s):  
Stephen A. Lauer ◽  
Krzysztof Sakrejda ◽  
Evan L. Ray ◽  
Lindsay T. Keegan ◽  
Qifang Bi ◽  
...  
Keyword(s):  
Public Health ◽  
Dengue Hemorrhagic Fever ◽  
Characteristic Curve ◽  
Model Performance ◽  
Hemorrhagic Fever ◽  
Absolute Error ◽  
Severe Bleeding ◽  
Severe Manifestation ◽  
Public Health Officials ◽  
Parsimonious Model

Dengue hemorrhagic fever (DHF), a severe manifestation of dengue viral infection that can cause severe bleeding, organ impairment, and even death, affects between 15,000 and 105,000 people each year in Thailand. While all Thai provinces experience at least one DHF case most years, the distribution of cases shifts regionally from year to year. Accurately forecasting where DHF outbreaks occur before the dengue season could help public health officials prioritize public health activities. We develop statistical models that use biologically plausible covariates, observed by April each year, to forecast the cumulative DHF incidence for the remainder of the year. We perform cross-validation during the training phase (2000–2009) to select the covariates for these models. A parsimonious model based on preseason incidence outperforms the 10-y median for 65% of province-level annual forecasts, reduces the mean absolute error by 19%, and successfully forecasts outbreaks (area under the receiver operating characteristic curve = 0.84) over the testing period (2010–2014). We find that functions of past incidence contribute most strongly to model performance, whereas the importance of environmental covariates varies regionally. This work illustrates that accurate forecasts of dengue risk are possible in a policy-relevant timeframe.

scholarly journals Dengue and Dengue Hemorrhagic Fever

1998 ◽  
Vol 11 (3) ◽  
pp. 480-496 ◽  
Author(s):  
Duane J. Gubler
Keyword(s):  
Public Health ◽  
Dengue Fever ◽  
Dengue Hemorrhagic Fever ◽  
Prevention And Control ◽  
Hemorrhagic Fever ◽  
Geographic Region ◽  
Control Programs ◽  
The Past ◽  
Public Health Officials ◽  
And Control

SUMMARY Dengue fever, a very old disease, has reemerged in the past 20 years with an expanded geographic distribution of both the viruses and the mosquito vectors, increased epidemic activity, the development of hyperendemicity (the cocirculation of multiple serotypes), and the emergence of dengue hemorrhagic fever in new geographic regions. In 1998 this mosquito-borne disease is the most important tropical infectious disease after malaria, with an estimated 100 million cases of dengue fever, 500,000 cases of dengue hemorrhagic fever, and 25,000 deaths annually. The reasons for this resurgence and emergence of dengue hemorrhagic fever in the waning years of the 20th century are complex and not fully understood, but demographic, societal, and public health infrastructure changes in the past 30 years have contributed greatly. This paper reviews the changing epidemiology of dengue and dengue hemorrhagic fever by geographic region, the natural history and transmission cycles, clinical diagnosis of both dengue fever and dengue hemorrhagic fever, serologic and virologic laboratory diagnoses, pathogenesis, surveillance, prevention, and control. A major challenge for public health officials in all tropical areas of the world is to devleop and implement sustainable prevention and control programs that will reverse the trend of emergent dengue hemorrhagic fever.

scholarly journals Dengue- aetiology and treatment

2017 ◽  
Vol 5 (01) ◽  
Author(s):  
Pushkar Singh Rawat ◽  
Kajal Patel ◽  
Sneha Srivastava ◽  
Sudhir Mehrotra
Keyword(s):  
Public Health ◽  
Dengue Fever ◽  
Dengue Hemorrhagic Fever ◽  
Prevention And Control ◽  
Hemorrhagic Fever ◽  
Geographic Region ◽  
Control Programme ◽  
Control Programs ◽  
Public Health Officials ◽  
And Control

Dengue fever, a very old disease, has re-emerged during past 20 years besides, an expanded geographic distribution of both the viruses and the mosquito vectors. With increased epidemic activity, the development of hyperendemicity (the co-circulation of multiple serotypes), and the emergence of dengue hemorrhagic fever in new geographic regions. In 1998 this mosquito-borne disease was the most important tropical infectious disease after malaria, with an estimated 100 million cases of dengue fever, 500,000 cases of dengue hemorrhagic fever, and 25,000 deaths annually. The reasons for this resurgence and emergence of dengue hemorrhagic fever in 21st century are complex and not fully understood, but demographic, societal, and public health infrastructure changes in the past 30 years have contributed greatly. Based on the data of National Vector Borne Disease Control Programme (NVBDCP), the number of cases reported in 2016 in India was about 1,11,880 for dengue with 227 deaths1. This paper reviews the changing epidemiology of dengue and dengue hemorrhagic fever by geographic region, the natural history and transmission cycles, clinical diagnosis of both dengue fever and dengue hemorrhagic fever, serologic and virologic laboratory diagnoses, pathogenesis, surveillance, prevention, and control. Major challenges for public health officials in all tropical areas of the world is to develop and implement sustainable prevention and control programs that will reverse the trend of emergent dengue hemorrhagic fever.

Difusi dan Pola Spasial Sebaran Penyakit Demam Berdarah Dengue (DBD) Di Kota Bandar Lampung

2018 ◽  
Vol 1 (1) ◽  
pp. 87-95
Author(s):  
Nurul Qamila ◽  
Agel Vidian Krama
Keyword(s):  
Public Health ◽  
Spatial Analysis ◽  
Aedes Aegypti ◽  
Dengue Virus ◽  
Spatial Pattern ◽  
Dengue Hemorrhagic Fever ◽  
Health Problem ◽  
Public Health Problem ◽  
Hemorrhagic Fever ◽  
Descriptive Method

Dengue hemorrhagic fever (DHF) is a contagious disease caused by the dengue virus and is transmitted by the mosquito Aedes aegypti (Aa.aegypti). The population is still a public health problem that increases the number of sufferers and also widespread, with population and education. This study aims to reveal the spatial pattern and distribution of Dengue Hemorrhagic Fever (DHF) with the spatial pattern and the spread of Dengue Hemorrhagic Fever (DHF) can result in different locations of these allegations. From the map that can be used for the prevention of Dengue Hemorrhagic Fever (DBD) in Bandar Lampung City. This study aims to reveal the spatial pattern and distribution of Dengue Hemorrhagic Fever (DHF) with the descriptive method and spatial pattern of Dengue Hemorrhagic Fever (DHF) can result in different locations of these allegations. From the map that can be used for the prevention of Dengue Hemorrhagic Fever (DBD) in Bandar Lampung City. Keywords: DHF, Spatial Analysis

COMMUNITY KNOWLEDGE OF DENGUE FEVER IN ALLAMA IQBAL TOWN, LAHORE

2020 ◽  
pp. 52-58
Author(s):  
OJS Admin
Keyword(s):  
Public Health ◽  
Dengue Fever ◽  
Dengue Hemorrhagic Fever ◽  
Health Problem ◽  
Public Health Problem ◽  
Hemorrhagic Fever ◽  
Community Knowledge

Globally, dengue is an emerging serious public health problem with a million infections occurring annually including significant number of dengue hemorrhagic fever cases.

scholarly journals Autokorelasi Spasial Demam Berdarah Dengue di Kecamatan Samarinda Utara, Kota Samarinda

2020 ◽  
Vol 19 (2) ◽  
pp. 119-126
Author(s):  
Syamsir Syamsir ◽  
Andi Daramusseng ◽  
Rudiman Rudiman
Keyword(s):  
Public Health ◽  
Spatial Autocorrelation ◽  
Health Center ◽  
Dengue Hemorrhagic Fever ◽  
Hemorrhagic Fever ◽  
Cluster Sampling ◽  
Spatial Autocorrelation Analysis ◽  
Z Score ◽  
Autocorrelation Analysis ◽  
Moran's I

Latar belakang: Demam Berdarah Dengue (DBD) masih menjadi masalah kesehatan masyarakat. Indonesia menjadi salah satu negara yang setiap tahunnya ditemukan kasus DBD. Program pengendalian DBD masih kurang maksimal karena puskesmas belum mampu memetakan wilayah rentan DBD. Penelitian ini bertujuan untuk mengetahui pola sebaran DBD di Kecamatan Samarinda Utara dengan menggunakan autokorelasi spasial.Metode: Penelitian ini dilaksanakan di kelurahan yang berada pada wilayah kerja Puskesmas Lempake, Kecamatan Samarinda Utara. Sampel penelitian dipilih berdasarkan metode cluster sampling. Berdasarkan kriteria jumlah kasus tertinggi maka kelurahan di Kecamatan Samarinda Utara yang representatif untuk dijadikan cluster pada penelitian ini yaitu kelurahan yang berada pada wilayah kerja Puskesmas Lempake. Analisis yang digunakan pada penelitian ini yaitu Spatial Autocorrelation Analysis dengan menggunakan metode Moran’s I. Spatial Autocorrelation Analysis digunakan untuk mengetahui apakah terdapat hubungan antar titik dan arah hubungannya (postif atau negatif).Hasil: Nilai Z-score atau Z hitung = 3,651181 dengan nilai kritis (Z α/2) sebesar 2,58. Ini menunjukkan bahwa Z-score > Z α/2 (3,6511 > 2,58) sehingga Ho ditolak. Terdapat autokorelasi spasial pada sebaran kasus DBD di wilayah kerja Puskesmas Lempake. Sebaran kasus DBD di wilayah kerja Puskesmas Lempake termasuk kategori clustered atau berkelompok pada lokasi tertentu. Moran’s Index (I) = 0,124420 artinya I > 0. Ini menunjukkan bahwa pola sebaran DBD di wilayah kerja Puskesmaas Lempake merupakan autokorelasi positif.    Simpulan: Pola sebaran kasus DBD di Kecamatan Samarinda Utara yaitu clustered. Autokorelasi spasial yang dihasilkan yaitu autokorelasi positif.  ABSTRACTTitle: Spatial Autocorrelation of Dengue Hemorrhagic Fever  in North Samarinda district, Samarinda CityBackground: Dengue Hemorrhagic Fever (DHF) is still a public health problem. Indonesia is one of the countries where DHF cases are found every year. The DHF control program is still less than optimal because the public health center has not been able to map the DHF vulnerable areas. This study aims to determine the pattern of DHF distribution in the District of North Samarinda by using spatial autocorrelation.Method: This research was conducted in a village located in the working area of the Lempake Health Center, Samarinda Utara district. The research sample was chosen based on the cluster sampling method. Based on the criteria for the highest number of cases, the representative village to be clustered in this study are the village within the working area of the Lempake Health Center. The analysis used in this study is spatial autocorrelation nalysis using the Moran’s I. Spatial autocorrelation Analysis method is used to determine whether there is a relationship between the point and direction of the relationship (positive or negative).Result: Z-score or Z count = 3.651181 with a critical value (Z α / 2) of 2.58. This shows that Z-score> Z α / 2 (3.6511> 2.58) so that Ho is rejected. There is a spatial autocorrelation in the distribution of dengue cases in the working area of the Lempake Health Center. The distribution of dengue cases in the working area of Lempake Health Center is classified as clustered or grouped in certain locations. Moran’s Index (I) = 0.124420 means I> 0. This shows that the pattern of DHF distribution in the work area of Lempake Health Center is a positive autocorrelation.Conclusion: The pattern of distribution of dengue cases in the District of North Samarinda is clustered. The resulting spatial autocorrelation is positive autocorrelation. 

scholarly journals Aplikasi Autoregressive Integrated Moving Average (ARIMA) untuk Meramalkan Jumlah Demam Berdarah Dengue (DBD) di Puskesmas Mulyorejo

2017 ◽  
Vol 5 (2) ◽  
pp. 177
Author(s):  
Luluk Nor Kasanah
Keyword(s):  
Public Health ◽  
Health Center ◽  
Dengue Hemorrhagic Fever ◽  
Moving Average ◽  
Arima Model ◽  
Hemorrhagic Fever ◽  
Small Error ◽  
Least Square ◽  
Public Health Center ◽  
Forecasting Method

ARIMA was one of a forecasting method of time series if independent variable be ignored, it would use the past and present value as a dependent variable. The accuracy of ARIMA forecasting method was good to produce short-term forecasting. The advantages of ARIMA method than other method was this method didn’t require the data pattern so it could be used for all kinds of data pattern, so it could be applied in cases of dengue hemorrhagic fever (DHF) in Mulyorejo Public Health Center. This study was to determine the best forecasting model as well as to predict and analyze the results of forecasting number of dengue hemorrhagic fever in Mulyorejo Public Health Center. The data was monthly number of dengue hemorrhagic fever patients in Mulyorejo Public Health Center from January 2010 to February 2016 (a total of 74 plots data). The results were the number of dengue hemorrhagic fever cases in Mulyorejo Public Health Center could be predicted with ARIMA model (1,0,0), thought based on diagnostics test the ARIMA model met all tests but the forecasting number of dengue hemorrhagic fever cases in years 2016–2017 showed a downward trend, and in 2017 was fl at, while MAPE and MAE amounted to 63.026% and 1.89%, the value of the error was large enough which indicated that less accurate forecasting. DHF data had a lot of missing data caused big value of MAPE and MAE so must be transformed by series mean method. DHF data was trend and seasonal so winters exponential smoothing with ordinary least square was better than ARIMA to get small error.

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

2021 ◽  
Vol 30 (4) ◽  
pp. 52-60
Author(s):  
Do Thi Thanh Toan ◽  
Nguyen Thanh Binh ◽  
Dao Huu Than ◽  
Nguyen Nhat Cam ◽  
Luu Ngoc Hoat ◽  
...  
Keyword(s):  
Public Health ◽  
Dengue Hemorrhagic Fever ◽  
Hemorrhagic Fever ◽  
Viral Disease ◽  
Public Health Issue ◽  
Cold Spot ◽  
Spatial Characteristics ◽  
Temporal And Spatial ◽  
Temporal And Spatial Characteristics ◽  
And Cluster Analysis

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.

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