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ISSN 2063-5346
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Disease Prediction in Real Time Based on Climate Data

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Dr.Nidha Z D Shafee, Dr.V.Sundaravel, Dr.Isaac Christian Mose, Dr.Mohamed Musthafa , Panneerselvam periasamy, Dr.Sasikala Gunasekaran
» doi: 10.48047/ecb/2023.12.si4.1205

Abstract

The weather can have a major impact on people's lives and welfare, even if no one can do anything to control it. disasters brought on by global warming. Furthermore, we are more susceptible to infectious diseases as a result of climate change. Global warming can affect infectious diseases in three main ways: the pathogen itself, the vector or host that spreads it, and the rate at which it spreads. The effects of climate change can be felt in all three of these ways. World Health Organisation (WHO) reports that 30 new diseases have been identified since 1996. Furthermore, arthropod-transmitted diseases including dengue fever, malaria, and chikungunya have made a resurgence and are rapidly expanding into formerly unaffected areas of the world. Factors like as precipitation, humidity, temperature, and others have various purposes in the transmission cycle. There is a chance that certain diseases will become more common if any of these conditions are changed. Early warning systems (EWS) for infectious diseases must account for the consequences of climate change, as evidenced by the rapid global spread of abroviral infections. In prior investigations, only weather records from the past were taken into account. The increasing levels of climate variability and unpredictability, on the other hand, are leading to the decline of traditional systems. In this research, we provide a method for predicting the number of new dengue cases over the next five days based on nothing but the weather forecast. Our findings have global relevance, and they pave the path for future research into specific daily disease outbreak scenarios through the use of real-time meteorological API. The purpose of this is to safeguard humanity from climate-related health hazards.

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