Luenam Amornrat, Puttanapong Nattapong
Faculty of Public and Environmental Health, Huachiew Chalermprakiet University, Samut Prakan.
Faculty of Economics, Thammasat University, Bangkok.
Geospat Health. 2022 Mar 18;17(s1). doi: 10.4081/gh.2022.1066.
This study statistically identified the localised association between socioeconomic conditions and the coronavirus disease 2019 (COVID-19) incidence rate in Thailand on the basis of the 1,727,336 confirmed cases reported nationwide during the first major wave of the pandemic (March-May 2020) and the second one (July 2021-September 2021). The nighttime light (NTL) index, formulated using satellite imagery, was used as a provincial proxy of monthly socioeconomic conditions. Local indicators of spatial association statistics were applied to identify the localised bivariate association between COVID-19 incidence rate and the year-on-year change of NTL index. A statistically significant negative association was observed between the COVID-19 incidence rate and the NTL index in some central and southern provinces in both major pandemic waves. Regression analyses were also conducted using the spatial lag model (SLM) and the spatial error model (SEM). The obtained slope coefficient, for both major waves of the pandemic, revealed a statistically significant negative association between the year-on-year change of NTL index and COVID-19 incidence rate (SLM: coefficient= âˆ'0.0078 and âˆ'0.0064 with P<0.001 and 0.056, respectively; and SEM: coefficient= âˆ'0.0086 and âˆ'0.0083 with P=0.067 and 0.056, respectively). All of the obtained results confirmed the negative association between the COVID-19 pandemic and socioeconomic activity revealing the future extensive applications of satellite imagery as an alternative data source for the timely monitoring of the multidimensional impacts of the pandemic.
本研究基于泰国在第一波疫情大流行期间(2020年3月至5月)和第二波疫情大流行期间(2021年7月至9月)全国报告的1,727,336例确诊病例,从统计学角度确定了社会经济状况与泰国2019冠状病毒病(COVID-19)发病率之间的局部关联。利用卫星图像制定的夜间灯光(NTL)指数被用作省级月度社会经济状况的替代指标。应用局部空间关联统计指标来确定COVID-19发病率与NTL指数同比变化之间的局部双变量关联。在两次主要疫情大流行期间,泰国中部和南部的一些省份,COVID-19发病率与NTL指数之间均观察到具有统计学意义的负相关。还使用空间滞后模型(SLM)和空间误差模型(SEM)进行了回归分析。在两次主要疫情大流行期间获得的斜率系数均显示,NTL指数同比变化与COVID-19发病率之间存在具有统计学意义的负相关(SLM:系数分别为−0.0078和−0.0064,P值分别<0.001和0.056;SEM:系数分别为−0.0086和−0.0083,P值分别为0.067和0.056)。所有获得的结果均证实了COVID-19大流行与社会经济活动之间的负相关,这表明卫星图像作为及时监测大流行多维影响的替代数据源具有广阔的应用前景。