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. 2020 Sep:98:153-160.
doi: 10.1016/j.ijid.2020.06.078. Epub 2020 Jun 30.

Spatiotemporal dynamics of the COVID-19 pandemic in the State of Kuwait

Moh A Alkhamis  1 , Sarah Al Youha  2 , Mohammad M Khajah  3 , Nour Ben Haider  4 , Sumayah Alhardan  2 , Ahmad Nabeel  2 , Sulaiman Al Mazeedi  2 , Salman K Al-Sabah  5
Affiliations

Spatiotemporal dynamics of the COVID-19 pandemic in the State of Kuwait

Moh A Alkhamis et al. Int J Infect Dis. 2020 Sep.

Abstract

Objectives: Prompt understanding of the temporal and spatial patterns of the COVID-19 pandemic on a national level is a critical step for the timely allocation of surveillance resources. Therefore, this study explored the temporal and spatiotemporal dynamics of the COVID-19 pandemic in Kuwait using daily confirmed case data collected between the 23 February and 07 May 2020.

Methods: The pandemic progression was quantified using the time-dependent reproductive number (R(t)). The spatiotemporal scan statistic model was used to identify local clustering events. Variability in transmission dynamics was accounted for within and between two socioeconomic classes: citizens-residents and migrant workers.

Results: The pandemic size in Kuwait continues to grow (R(t)s ≥2), indicating significant ongoing spread. Significant spreading and clustering events were detected among migrant workers, due to their densely populated areas and poor living conditions. However, the government's aggressive intervention measures have substantially lowered pandemic growth in migrant worker areas. However, at a later stage of the study period, active spreading and clustering events among both socioeconomic classes were found.

Conclusions: This study provided deeper insights into the epidemiology of COVID-19 in Kuwait and provided an important platform for rapid guidance of decisions related to intervention activities.

Keywords: COVID-19; Migrant worker; Spatiotemporal cluster; Surveillance; Time-dependent reproductive number.

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Figures

Figure 1
Figure 1
Temporal distribution of daily COVID-19 confirmed cases between 23 February and 07 May 2020 in the State of Kuwait.
Figure 2
Figure 2
Time-dependent reproductive numbers (R(t)) and model-predicted incidences of COVID-19 cases in the State of Kuwait between 23 February and 07 May 2020. (A, C, and E) Blue lines indicate the calculated R(t)s; light blue shaded areas indicate their 95% confidence intervals (CI); and the magenta lines indicate R(t)s = 1. (B, D, and F) Gray lines indicate the daily observed cases, while the red lines indicate the predicted incidences by the R(t) model. (A and B) indicate the results for the state of Kuwait. (C and D) indicate results for citizens and residents. (E and F) indicate results for migrant workers. The red arrow indicates the highest number of daily secondary cases throughout the study period (R(t) = 3.5).
Figure 3
Figure 3
Geographical distribution of COVID-19 cases and their most likely significant spatiotemporal clusters in the State of Kuwait between 23 February and 07 May 2020. (A) Spatially smoothed geographical locations of confirmed cases by a kernel density function (case per 5 m2). The green square indicates the Aljleeb neighborhood, while the purple square indicates the Mahboula neighborhood. (B) Significant clusters identified by the retrospective scan statistic model. (C) Significant clusters identified by the prospective scan statistic model. The radius of the circles (km2) is proportional to the predicted spatial extent of a given cluster. The clusters are rank-ordered according to their significance (1 = the primary most likely cluster). Confounded clusters indicate clusters caused by both migrant workers and citizen/resident cases.
See this image and copyright information in PMC

References

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