The effects of maximum ambient temperature and heatwaves on dengue infections in the tropical city-state of Singapore – A time series analysis

Seah, Annabel; Aik, Joel; Ng, Lee Ching; Tam, Clarence C.

doi:10.1016/j.scitotenv.2021.145117

Cited by 26 publications

(29 citation statements)

References 55 publications

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“…The difference in the direction of association at the different lags is likely attributable to the generation interval distribution, in which the average infectiousness profile of dengue first increases and then decreases with time. More importantly, although dengue cases were known to be affected by the weather [41][42][43][44], we found no residual relationship between climate factors and dengue transmissibility once disease case counts were controlled for.…”

Section: Discussionmentioning

confidence: 58%

Fine-scale estimation of effective reproduction numbers for dengue surveillance

et al. 2022

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The effective reproduction number Rt is an epidemiological quantity that provides an instantaneous measure of transmission potential of an infectious disease. While dengue is an increasingly important vector-borne disease, few have used Rt as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of Rt for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010–2020, we estimated Rt by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of Rt from each proposed method and determined exogenous temporal and spatial drivers for Rt in relation to a wide range of environmental and anthropogenic factors. At the national level, both methods achieved satisfactory model performance (R2EpiEstim = 0.95, R2EpiFilter = 0.97), but disparities in performance were large at finer spatial scales when case counts are low (MASE EpiEstim = 1.23, MASEEpiFilter = 0.59). Impervious surfaces and vegetation with structure dominated by human management (without tree canopy) were positively associated with increased transmission intensity. Vegetation with structure dominated by human management (with tree canopy), on the other hand, was associated with lower dengue transmission intensity. We showed that dengue outbreaks were preceded by sustained periods of high transmissibility, demonstrating the potential of Rt as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of Rt at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response.

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Section: Discussionmentioning

confidence: 58%

Fine-scale estimation of effective reproduction numbers for dengue surveillance

et al. 2022

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“…In comparison with the literature, we see that, in general, higher temperature is related to an augmented RR of mortality and hospitalisation by any causes 2,3,22,23 . There is scarce literature on the association between temperatures and hospitalisation by an infectious disease.…”

Section: Discussionmentioning

confidence: 56%

“…Dengue fever has been a major global seasonal endemic disease, mainly present in the tropics, with an estimated burden over ~390 million infections per year. [1][2][3][4] Approximately one-quarter of these infections manifest as clinical or subclinical disease. 1 Brazil is one of the most affected countries by Dengue, that has caused over ~20•9 million cases of infections in the last 20 years, since the compulsory universal notification to the Brazilian health systems was established.…”

Section: Introductionmentioning

confidence: 99%

“…The pathophysiology of Dengue severity involves dehydration and coagulation disorders, both conditions that can be aggravated by ambient temperature. 8,9 Based on the extensive literature on the association of temperature and all-cause hospitalizations, 2,3,5,6 we hypothesised that high ambient temperatures are associated with a higher risk of hospitalisation due to Dengue. We aimed to evaluate the association between ambient temperature and Dengue hospitalisation in Brazil, analysing the period from 2010 to 2019.…”

Section: Introductionmentioning

confidence: 99%

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Ambient Temperature and Dengue Hospitalisation in Brazil: A 10-year period two-stage case-design time series analysis

Silva

Basagaña

Bastos

et al. 2022

Preprint

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Background: Climate factors are known to influence seasonal patterns of dengue transmission However, little is known about the effect of extreme heat on the severity of dengue infection, such as hospital admission. We aimed to quantify the effect of ambient temperature on dengue hospitalisation risk in Brazil Methods: We retrieved daily dengue hospitalisation counts by each of 5,570 municipalities across the 27 states of Brazil from 1st of January 2010 to 31st of December 2019, from the Brazilian Public Hospital Admission System (SIH). We obtained average daily ambient temperature for each municipality from the ERA5-land product reanalysis. We combined distributed lag non-linear models with time stratified design model framework to pool an estimate for dose-response and lag-response structures for the association of Dengue hospitalisation relative risk (RR) and temperature. We estimated the overall dengue hospitalisation RR for the whole country as well as for each of the five macro-regions by meta- analysing state level estimates. Findings: 579,703 hospital admissions due to dengue occurred over the 10 years period of 2010 to 2019. We observed a positive association between high temperatures and high risk of hospitalisation for Brazil and each of the five macro-regions. The overall RR for dengue hospitalisation was at the 50th percentile of temperature distribution 1.40 (95% IC 1.27-1.54) and at 95th percentile of temperature the RR was 1.50 (1.38-1.66) for Brazil, relative to the minimum temperature, which was the one with the lowest risk. We also found lagged effects of heat on hospitalisation, particularly observed on the same day (lag 0) both at the 50th percentile and 95th. Interpretation: High temperatures are associated with an increase in the risk of hospitalisation by dengue infection. These findings may guide preparedness and mitigation policies during dengue season outbreaks, particularly on the health-care demand.

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“…A large number of cases of DHF can be attributed to temperature [40], [41], [42]. Climatic factors such as temperature, humidity, and rainfall [43], [44], [45] [46] can prolong the transmission period of DHF [47]. Temperatures of 24-39°C play a significant role in mosquitoes' development, survival, and feeding behavior to promote viral replication in vectors [48]; thus, DHF will increase by 35% per 1°C [49].…”

Section: The Incidence Rate Of Dhf Based On Climatic Factorsmentioning

confidence: 99%

Impact of Climate Variability and Incidence on Dengue Hemorrhagic Fever in Palembang City, South Sumatra, Indonesia

Rubel

Anwar

Irfanuddin

et al. 2021

Open Access Maced J Med Sci

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Dengue hemorrhagic fever (DHF) is a dengue virus infection transmitted by Aedes spp. Climate has a profound influence on mosquito breeding. Palembang has the highest rate of DHF in South Sumatra. This study aimed to investigate the relationship between the components of climate factors and the incidence of DHF in Palembang. This study was cross-sectional, with an observational analytic approach. The Palembang City Health Office compiled data on DHF incidence rates from 2016 to 2020. Climatic factor data (rainfall, number of rainy days, temperature, humidity, wind speed, sun irradiance) were collected from the Climatology Station Class I Palembang - BMKG Station and Task Force that same year. The Spearman test was used to conduct the correlation test. Between 2016 and 2020, there were 3,398 DHF patients. From January to May, DHF increased. There was a significant correlation between rainfall (r = 0.320; p = 0.005), number of rainy days (r = 0.295; p = 0.020), temperature (r = 0.371; p = 0.040), and humidity (r = 0.221; p = 0.024), wind speed (r= 0.76; p = 0.492), and sunlight (r = 0.008; p = 0.865). Rainfall, the number of rainy days, and temperature were three climatic factors determining the increase in dengue incidence in Palembang.

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The effects of maximum ambient temperature and heatwaves on dengue infections in the tropical city-state of Singapore – A time series analysis

Cited by 26 publications

References 55 publications

Fine-scale estimation of effective reproduction numbers for dengue surveillance

Fine-scale estimation of effective reproduction numbers for dengue surveillance

Ambient Temperature and Dengue Hospitalisation in Brazil: A 10-year period two-stage case-design time series analysis

Impact of Climate Variability and Incidence on Dengue Hemorrhagic Fever in Palembang City, South Sumatra, Indonesia

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