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Lag effect of climatic variables on dengue burden in India.

ABSTRACT: Dengue is a widespread vector-borne disease believed to affect between 100 and 390 million people every year. The interaction between vector, host and pathogen is influenced by various climatic factors and the relationship between dengue and climatic conditions has been poorly explored in India. This study explores the relationship between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and dengue cases in India. Additionally, distributed lag non-linear model was used to assess the delayed effects of climatic factors on dengue cases. The weekly dengue cases reported by the Integrated Disease Surveillance Program (IDSP) over India during the period 2010-2017 were analysed. The study shows that dengue cases usually follow a seasonal pattern, with most cases reported in August and September. Both temperature and rainfall were positively associated with the number of dengue cases. The precipitation shows the higher transmission risk of dengue was observed between 8 and 15 weeks of lag. The highest relative risk (RR) of dengue was observed at 60 mm rainfall with a 12-week lag period when compared with 40 and 80 mm rainfall. The RR of dengue tends to increase with increasing mean temperature above 24 °C. The largest transmission risk of dengue was observed at 30 °C with a 0-3 weeks of lag. Similarly, the transmission risk increases more than twofold when the minimum temperature reaches 26 °C with a 2-week lag period. The dengue cases and El Niño were positively correlated with a 3-6 months lag period. The significant correlation observed between the IOD and dengue cases was shown for a 0-2 months lag period.

SUBMITTER: Kakarla SG

PROVIDER: S-EPMC6518529 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Lag effect of climatic variables on dengue burden in India.

Kakarla Satya Ganesh SG Caminade Cyril C Mutheneni Srinivasa Rao SR Morse Andrew P AP Upadhyayula Suryanaryana Murty SM Kadiri Madhusudhan Rao MR Kumaraswamy Sriram S

Epidemiology and infection 20190101

Dengue is a widespread vector-borne disease believed to affect between 100 and 390 million people every year. The interaction between vector, host and pathogen is influenced by various climatic factors and the relationship between dengue and climatic conditions has been poorly explored in India. This study explores the relationship between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and dengue cases in India. Additionally, distributed lag non-linear model was used to asses ...[more]

PMID: 31063099

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Project description:Globally, since the end of December 2019, coronavirus disease (COVID-19) has been recognized as a severe infectious disease. Therefore, this study has been attempted to examine the linkage between climatic variables and COVID-19 particularly in National Capital Territory of Delhi (NCT of Delhi), India. For this, daily data of COVID-19 has been used for the period March 14 to June 11, 2020, (90 days). Eight climatic variables such as maximum, minimum and mean temperature (°C), relative humidity (%), bright sunshine hours, wind speed (km/h), evaporation (mm), and rainfall (mm) have been analyzed in relation to COVID-19. To study the relationship among different climatic variables and COVID-19 spread, Karl Pearson’s correlation analysis has been performed. The Mann–Kendall method and Sen’s slope estimator have been used to detect the direction and magnitude of COVID-19 trends, respectively. The results have shown that out of eight selected climatic variables, six variables, viz. maximum temperature, minimum temperature, mean temperature, relative humidity, evaporation, and wind speed are positively associated with coronavirus disease cases (statistically significant at 95 and 99% confidence levels). No association of coronavirus disease has been found with bright sunshine hours and rainfall. Besides, COVID-19 cases and deaths have shown increasing trends, significant at 99% confidence level. The results of this study suggest that climatic conditions in NCT of Delhi are favorable for COVID-19 and the disease may spread further with the increasing temperature, relative humidity, evaporation and wind speed. This is the only study which has presented the analysis of COVID-19 spread in relation to several climatic variables for the most densely populated and rapidly growing city of India. Thus, considering the results obtained, effective policies and actions are necessary especially by identifying the areas where the spread rate is increasing rapidly in this megacity. The prevention and protection measures should be adopted aiming at to reduce the further transmission of disease in the city.

Project description:BackgroundClimate change is an important driver of the increased spread of dengue from tropical and subtropical regions to temperate areas around the world. Climate variables such as temperature and precipitation influence the dengue vector's biology, physiology, abundance, and life cycle. Thus, an analysis is needed of changes in climate change and their possible relationships with dengue incidence and the growing occurrence of epidemics recorded in recent decades.ObjectivesThis study aimed to assess the increasing incidence of dengue driven by climate change at the southern limits of dengue virus transmission in South America.MethodsWe analyzed the evolution of climatological, epidemiological, and biological variables by comparing a period of time without the presence of dengue cases (1976-1997) to a more recent period of time in which dengue cases and important outbreaks occurred (1998-2020). In our analysis, we consider climate variables associated with temperature and precipitation, epidemiological variables such as the number of reported dengue cases and incidence of dengue, and biological variables such as the optimal temperature ranges for transmission of dengue vector.ResultsThe presence of dengue cases and epidemic outbreaks are observed to be consistent with positive trends in temperature and anomalies from long-term means. Dengue cases do not seem to be associated with precipitation trends and anomalies. The number of days with optimal temperatures for dengue transmission increased from the period without dengue cases to the period with occurrences of dengue cases. The number of months with optimal transmission temperatures also increased between periods but to a lesser extent.ConclusionsThe higher incidence of dengue virus and its expansion to different regions of Argentina seem to be associated with temperature increases in the country during the past two decades. The active surveillance of both the vector and associated arboviruses, together with continued meteorological data collection, will facilitate the assessment and prediction of future epidemics that use trends in the accelerated changes in climate. Such surveillance should go hand in hand with efforts to improve the understanding of the mechanisms driving the geographic expansion of dengue and other arboviruses beyond the current limits. https://doi.org/10.1289/EHP11616.

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Lag effect of climatic variables on dengue burden in India.

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Lag effect of climatic variables on dengue burden in India.

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