“…Figures 3 and 4 shows this result, which shows an average correlation between relative humidity and confirmed cases of dengue and a low correlation between the variables relative air temperature and precipitation. Although several authors 43 claim that the variables air temperature and precipitation have a direct influence on the incidence of dengue, in the city of Alagoinhas these variables are a little less relevant than humidity. Figure 3 The DCCA between temperature, humidity and precipitation and dengue cases show that there is a positive correlation between humidity and dengue cases and a negative correlation with temperature and precipitation.…”
The Aedes aegypti mosquito is the main vector of dengue and is a synanthropic insect and due to its anthropophilic nature, it has specific reproductive needs. In addition to that, it also needs tropical regions that provide climate-prone conditions that favor vector development. In this article, we propose the cross-correlation analysis between the climatic variables air temperature, relative humidity, weekly average precipitation and dengue cases in the period from 2017 to early 2021 in the municipality of Alagoinhas, Bahia, Brazil. To do so, we apply the trend-free cross-correlation, $$\rho DCCA$$
ρ
D
C
C
A
, being a generalization of the fluctuation analysis without trend, where we calculate the cross correlation between time series to establish the influence of these variables on the occurrence of dengue disease. The results obtained here were a moderate correlation between relative humidity and the incidence of dengue cases, and a low correlation for relative air temperature and precipitation. However, the predominant factor in the incidence of dengue cases in the city of Alagoinhas is relative humidity and not air temperature and precipitation.
“…Figures 3 and 4 shows this result, which shows an average correlation between relative humidity and confirmed cases of dengue and a low correlation between the variables relative air temperature and precipitation. Although several authors 43 claim that the variables air temperature and precipitation have a direct influence on the incidence of dengue, in the city of Alagoinhas these variables are a little less relevant than humidity. Figure 3 The DCCA between temperature, humidity and precipitation and dengue cases show that there is a positive correlation between humidity and dengue cases and a negative correlation with temperature and precipitation.…”
The Aedes aegypti mosquito is the main vector of dengue and is a synanthropic insect and due to its anthropophilic nature, it has specific reproductive needs. In addition to that, it also needs tropical regions that provide climate-prone conditions that favor vector development. In this article, we propose the cross-correlation analysis between the climatic variables air temperature, relative humidity, weekly average precipitation and dengue cases in the period from 2017 to early 2021 in the municipality of Alagoinhas, Bahia, Brazil. To do so, we apply the trend-free cross-correlation, $$\rho DCCA$$
ρ
D
C
C
A
, being a generalization of the fluctuation analysis without trend, where we calculate the cross correlation between time series to establish the influence of these variables on the occurrence of dengue disease. The results obtained here were a moderate correlation between relative humidity and the incidence of dengue cases, and a low correlation for relative air temperature and precipitation. However, the predominant factor in the incidence of dengue cases in the city of Alagoinhas is relative humidity and not air temperature and precipitation.
“…Transmission of DENV occurs in a seasonal pattern, and several climate variables have been found to increase DENV transmission and/or vector populations ( 17 – 19 , 35 , 36 ). While prior studies have demonstrated associations between climate variables like average precipitation, relative humidity, temperature, and wind speed, with varying lag times between 0 and 3 months, and dengue incidence ( 37 – 40 ), our predictive-based analytic framework is not intended to examine causal or associative relationships between climate variables and the outcome of dengue incidence. Our findings suggest that site-specific climate variables aid in site-specific models to predict DENV infection.…”
The differentiation of dengue virus (DENV) infection, a major cause of acute febrile illness in tropical regions, from other etiologies, may help prioritize laboratory testing and limit the inappropriate use of antibiotics. While traditional clinical prediction models focus on individual patient-level parameters, we hypothesize that for infectious diseases, population-level data sources may improve predictive ability. To create a clinical prediction model that integrates patient-extrinsic data for identifying DENV among febrile patients presenting to a hospital in Thailand, we fit random forest classifiers combining clinical data with climate and population-level epidemiologic data. In cross-validation, compared to a parsimonious model with the top clinical predictors, a model with the addition of climate data, reconstructed susceptibility estimates, force of infection estimates, and a recent case clustering metric significantly improved model performance.
“…Also, the divisions in the south of Dhaka had 0.92 °C higher temperature (27.46 vs 26.54 °C, p<0.01) compared to the divisions in the north to Dhaka. Higher temperature has been associated with increased dengue cases because of its impact on the extrinsic incubation period of the virus and the increased biting rate of the mosquitoes [2,27,28]. However, it might be possible that a higher incidence of dengue cases in southern districts is an artifact of economic development in the regions which helped people visit healthcare facilities more frequently than their northern counterparts [29].…”
Section: Discussionmentioning
confidence: 99%
“…Our model also showed that the ratio of urban and rural population which we used as a proxy to indicate urbanization had an increased risk of having more dengue cases. We found a conflicting negative association between rainfall and dengue cases [28], which might be because of higher rainfall in the Sylhet division where the highest amount of precipitation is recorded in Bangladesh. However, the relative humidity was positively associated with increased dengue cases as has been seen elsewhere [28].…”
In 2023, Bangladesh experienced its largest and deadliest outbreak of Dengue virus (DENV), reporting the highest-ever recorded annual cases and deaths. We aimed to characterize the geographical transmission of the DENV in Bangladesh. From 1 Jan - 31 Dec 2023, we extracted and analyzed daily data on dengue cases and deaths from the national Management Information System (MIS). We performed a generalized linear mixed model to identify the associations between division-wise daily dengue counts and various geographical and meteorological covariates. The number of Dengue cases reported in 2023 was 1.3 times higher than the total number recorded in the past 23 years (321,179 vs. 244,246), with twice as many deaths than the total fatalities recorded in the past 23 years (1705 vs. 849). Of the 1705 deaths in 2023, 67.4% (n=1015) expired within one day after hospital admission. The divisions southern to Dhaka had a higher dengue incidence/1000 population (2.30 vs. 0.50, p<0,0.01), and higher mean annual temperatures (27.46 vs. 26.54 °C) than the northern divisions. The average daily temperature (IRR: 1.13, 95% CI: 1.11-1.14), urban and rural population ratio of the divisions (IRR: 1.04, 95% CI: 1.03-1.04), showed a positive, and rainfall (IRR: 0.99, 95% CI: 0.98-0.99) showed a negative association with dengue cases in each division. We observed a major geographical shift of Dengue cases from the capital city Dhaka to different districts of Bangladesh with a higher incidence of dengue in the southern division of Bangladesh, influenced by temperature and urbanization.
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