Spatial temporal variation of dengue spread in different agro climatic zones of Tamil Nadu, India

Jaisankar, R.; Kesavan, J

doi:10.1063/5.0016987

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…Spatial analysis is vital in mapping the spread of various diseases and assists in policy making, especially in the era of the COVID-19 pandemic. The spatial variations through QGIS was shown in temporal trends of dengue incidences in Tamil Nadu ( 32 ). Animal bites were mapped through GPS and google earth ( 33 ).…”

Section: Discussionmentioning

confidence: 99%

Spatial Mapping the Dengue and Chikungunya Burden in a Rural Area near Bangalore- a Descriptive Cross-Sectional Study

Nugehally-Raju,

Gattam

2024

JAD

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Background: The burden of dengue and chikungunya diseases across geographical regions of India is poorly quantified more so during Covid19 pandemic and from hospital-based studies. The objective was to assess the prevalence of dengue and chikungunya in the study mainly area and to visualize the spatial distribution of dengue and chikungunya cases using the Quantum Geographic Information System (QGIS). Methods: This descriptive cross-sectional study was conducted among the population in villages coming under a medical college’s rural field practice area near Bangalore. A total of 31 villages were selected through a simple random sampling method and 3356 subjects were surveyed through household visits. QGIS was used for spatial mapping of cases. Results: 3356 subjects were surveyed, and the prevalence of dengue and chikungunya was 1.13% and 0.02%, respectively. The overall prevalence of dengue and chikungunya cases together was 1.16%. All 39 (100%) cases had reported fever and 31 cases (79.5%) reported myalgia followed by arthralgia 22 (56.4%). QGIS supported spatial mapping of the cases and no clustering of cases was found in the study area. Conclusion: The burden of dengue and chikungunya is under reported, and the surveillance system needs to be strengthened in the rural area. QGIS was found to be useful in the spatial mapping of the cases and there was no clustering of cases observed.

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Section: Discussionmentioning

confidence: 99%

Spatial Mapping the Dengue and Chikungunya Burden in a Rural Area near Bangalore- a Descriptive Cross-Sectional Study

Nugehally-Raju,

Gattam

2024

JAD

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“…We call the internal temporal trend (ITT) the change in the event’s temporal trend within a cluster, and the external temporal trend (ETT) the trend of all other areas that do not belong to this cluster. Therefore, what is statistically significant in this analysis is the temporal trends, rather than the cluster formation, as in spatial and spatiotemporal scanning [ 26 , 27 ].…”

Section: Methodsmentioning

confidence: 99%

International Migration, Refugees, and Spread of Tuberculosis in Brazil: Analysis of Clusters, Trends, and Associated Factors (2010–2021)

Alves,

Berra,

Tavares

et al. 2024

TropicalMed

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Background: International migration is a global phenomenon with significant implications on the health–disease process due to exposures along transit routes and local/destination epidemiological indicators. We aimed to analyze the transmission and spread of tuberculosis among international migrants and refugees from a spatiotemporal perspective and the associated factors. Method: This was an ecological study of cases of tuberculosis in international migrants in Brazil, between 2010 and 2021. Annual incidence rates were calculated and spatiotemporal scan techniques were used to identify municipalities at risk. Multiple logistic regression was used to identify factors associated with tuberculosis in international migrants. Results: A total of 4037 cases of tuberculosis were reported in Brazil in international migrants. Municipalities at risk for this event were identified using the spatiotemporal scan technique, and a cluster was identified with ITT: +52.01% and ETT: +25.60%. A higher probability of TB infection was identified in municipalities with a TB incidence rate >14.40 cases/100 inhabitants, population >11,042 inhabitants, Gini index >0.49, and illiteracy rate >13.12%. A lower probability was found in municipalities with average per capita household income >BRL 456.43. Conclusions: It is recommended that health authorities implement monitoring and rigorous follow-up in affected areas to ensure proper diagnosis and treatment completion for international migrants, preventing disease spread to other communities.

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Spatial temporal variation of dengue spread in different agro climatic zones of Tamil Nadu, India

Cited by 2 publications

References 11 publications

Spatial Mapping the Dengue and Chikungunya Burden in a Rural Area near Bangalore- a Descriptive Cross-Sectional Study

Spatial Mapping the Dengue and Chikungunya Burden in a Rural Area near Bangalore- a Descriptive Cross-Sectional Study

International Migration, Refugees, and Spread of Tuberculosis in Brazil: Analysis of Clusters, Trends, and Associated Factors (2010–2021)

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