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. 2022 Aug 8;7(8):171.
doi: 10.3390/tropicalmed7080171.

Temporal Variations and Spatial Clusters of Dengue in Thailand: Longitudinal Study before and during the Coronavirus Disease (COVID-19) Pandemic

Sayambhu Saita  1   2 , Sasithan Maeakhian  3 , Tassanee Silawan  4
Affiliations

Temporal Variations and Spatial Clusters of Dengue in Thailand: Longitudinal Study before and during the Coronavirus Disease (COVID-19) Pandemic

Sayambhu Saita et al. Trop Med Infect Dis. .

Abstract

The efforts towards effective control of the COVID-19 pandemic may affect the incidence of dengue. This study aimed to investigate temporal variations and spatial clusters of dengue in Thailand before and during the COVID-19 pandemic. Reported dengue cases before (2011-2019) and during (2020-2021) the COVID-19 pandemic were obtained from the national disease surveillance datasets. The temporal variations were analyzed using graphics, a seasonal trend decomposition procedure based on Loess, and Poisson regression. A seasonal ARIMA model was used to forecast dengue cases. Spatial clusters were investigated using the local indicators of spatial associations (LISA). The cyclic pattern showed that the greatest peak of dengue cases likely changed from every other year to every two or three years. In terms of seasonality, a notable peak was observed in June before the pandemic, which was delayed by one month (July) during the pandemic. The trend for 2011-2021 was relatively stable but dengue incidence decreased dramatically by 7.05% and 157.80% on average in 2020 and 2021, respectively. The forecasted cases in 2020 were slightly lower than the reported cases (2.63% difference), whereas the forecasted cases in 2021 were much higher than the actual cases (163.19% difference). The LISA map indicated 5 to 13 risk areas or hotspots of dengue before the COVID-19 pandemic compared to only 1 risk area during the pandemic. During the COVID-19 pandemic, dengue incidence sharply decreased and was lower than forecasted, and the spatial clusters were much lower than before the pandemic.

Keywords: COVID-19; coronavirus disease; dengue; spatial clusters; temporal variations.

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Conflict of interest statement

The authors declare no conflict of interest. The funders for APC had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Map of the 77 provinces in Thailand, including the Bangkok Metropolitan Administration.
Figure 2
Figure 2
Dengue incidence before (black line) and during the COVID-19 pandemic (red line). The red dots represent the beginning of the COVID-19 pandemic in Thailand.
Figure 3
Figure 3
Seasonal pattern of dengue incidence. Seasonal boxplot before; the circles refer to outlier values (a) and during (b) the COVID-19 pandemic.
Figure 4
Figure 4
The STL of dengue incidence in Thailand from 2011 to 2021; raw data (top), seasonal component (second from top), trend component (third from top), and residual or remainder (bottom). The red dots represent the beginning of the COVID-19 pandemic in Thailand.
Figure 5
Figure 5
Forecasted dengue cases in 2020–2021 (blue dots), and dengue cases before (black line) and during the COVID-19 pandemic (red line).
Figure 6
Figure 6
Forecasted dengue cases in 2022 (blue dots), and dengue cases before (black line) and during the COVID-19 pandemic (red line) (a). An enlarged view of forecasted dengue cases in 2022 (b).
Figure 7
Figure 7
Map of the incidence rates (top) and the SEB-smoothed rates (bottom) of dengue before and during the COVID-19 pandemic. The red dots represent the beginning of the COVID-19 pandemic in Thailand.
Figure 8
Figure 8
Map of the local indicators of spatial association (LISA) of the SEB-smoothed rates of dengue before and during the COVID-19 pandemic: high–high (red); low–low (blue); low–high (pale blue); high–low (pink). The red dots represent the beginning of the COVID-19 pandemic in Thailand.
See this image and copyright information in PMC

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