Thousands of lives are lost every year in developing countries for failing to detect epidemics early because of the lack of real-time disease surveillance data. We present results from a large-scale deployment of a telephone triage service as a basis for dengue forecasting in Pakistan. Our system uses statistical analysis of dengue-related phone calls to accurately forecast suspected dengue cases 2 to 3 weeks ahead of time at a subcity level (correlation of up to 0.93). Our system has been operational at scale in Pakistan for the past 3 years and has received more than 300,000 phone calls. The predictions from our system are widely disseminated to public health officials and form a critical part of active government strategies for dengue containment. Our work is the first to demonstrate, with significant empirical evidence, that an accurate, location-specific disease forecasting system can be built using analysis of call volume data from a public health hotline.
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http://dx.doi.org/10.1126/sciadv.1501215 | DOI Listing |
Sci Rep
January 2025
Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany.
The global burden of dengue disease is escalating under the influence of climate change, with India contributing a third of the total. The non-linearity and regional heterogeneity inherent in the climate-dengue relationship and the lack of consistent data makes it difficult to make useful predictions for effective disease prevention. The current study investigates these non-linear climate-dengue links in Pune, a dengue hotspot region in India with a monsoonal climate and presents a model framework for predicting both the near-term and future dengue mortalities.
View Article and Find Full Text PDFEcotoxicol Environ Saf
January 2025
Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, Shandong, PR China.
Dengue, a climate-sensitive mosquito-borne viral disease, is endemic in many tropical and subtropical areas, with Southeast Asia bearing the highest burden. In China, dengue epidemics are primarily influenced by imported cases from Southeast Asia. By integrating monthly maximum temperature and precipitation from Southeast Asia and local provinces in China, we aim to build models to predict dengue incidence in high-risk areas of China.
View Article and Find Full Text PDFMath Biosci Eng
December 2024
Department of Mathematics, New Mexico Tech, New Mexico 87801, USA.
We present a modeling strategy to forecast the incidence rate of dengue in the department of Córdoba, Colombia, thereby considering the effect of climate variables. A Seasonal Autoregressive Integrated Moving Average model with exogenous variables (SARIMAX) model is fitted under a cross-validation approach, and we examine the effect of the exogenous variables on the performance of the model. This study uses data of dengue cases, precipitation, and relative humidity reported from years 2007 to 2021.
View Article and Find Full Text PDFEur J Public Health
January 2025
Public Health and Community Medicine Department, Faculty of Medicine, Cairo University, Cairo, Egypt.
Dengue fever is considered as an emerging disease in Afghanistan. Since the first outbreak was reported in 2019, other outbreaks have been reported in the following years. The current study aims to describe the epidemiological features and clinical manifestations of suspected and confirmed cases of dengue fever detected by the National Disease Surveillance and Response (NDSR) Department of the Ministry of Public Health (MoPH) during 2021 and 2022 to prevent further spread and minimize its impact on the country's health system and on the limited number of health workers.
View Article and Find Full Text PDFExpert Rev Anti Infect Ther
January 2025
Center for Global Health Research, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
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