Islam Ariful, Sayeed Md Abu, Rahman Md Kaisar, Ferdous Jinnat, Shano Shahanaj, Choudhury Shusmita Dutta, Hassan Mohammad Mahmudul
EcoHealth Alliance New York, NY 10001-2320, USA.
Centre for Integrative Ecology, School of Life and Environmental Science, Deakin University, Victoria 3216, Australia.
Biosaf Health. 2021 Feb;3(1):39-49. doi: 10.1016/j.bsheal.2020.09.006. Epub 2020 Sep 23.
South Asian (SA) countries have been fighting with the pandemic novel coronavirus disease 2019 (COVID-19) since January 2020. Earlier, the country-specific descriptive study has been done. Nevertheless, as transboundary infection, the border sharing, shared cultural and behavioral practice, effects on the temporal and spatial distribution of COVID-19 in SA is still unveiled. Therefore, this study has been revealed the spatial hotspot along with descriptive output on different parameters of COVID-19 infection. We extracted data from the WHO and the worldometer database from the onset of the outbreak up to 15 May, 2020. Europe has the highest case fatality rate (CFR, 9.22%), whereas Oceania has the highest (91.15%) recovery rate from COVID-19. Among SA countries, India has the highest number of cases (85,790), followed by Pakistan (38,799) and Bangladesh (20,065). However, the number of tests conducted was minimum in this region in comparison with other areas. The highest CFR was recorded in India (3.21%) among SA countries, whereas Nepal and Bhutan had no death record due to COVID-19 so far. The recovery rate varies from 4.75% in the Maldives to 51.02% in Sri Lanka. In Bangladesh, community transmission has been recorded, and the highest number of cases were detected in Dhaka, followed by Narayanganj and Chattogram. We detected Dhaka and its surrounding six districts, namely Gazipur, Narsingdi, Narayanganj, Munshiganj, Manikganj, and Shariatpur, as the 99% confidence-based hotspot where Faridpur and Madaripur district as the 95% confidence-based spatial hotspots of COVID-19 in Bangladesh. However, we did not find any cold spots in Bangladesh. We identified three hotspots and three cold spots at different confidence levels in India. Findings from this study suggested the "Test, Trace, and Isolation" approach for earlier detection of infection to prevent further community transmission of COVID-19.
自2020年1月以来,南亚国家一直在与新型冠状病毒肺炎(COVID-19)疫情作斗争。此前,已开展了针对各国的描述性研究。然而,作为跨境感染,边境共享、共同的文化和行为习惯对南亚地区COVID-19时空分布的影响仍不明确。因此,本研究揭示了COVID-19感染不同参数的空间热点以及描述性结果。我们从世界卫生组织(WHO)和世界ometers数据库中提取了从疫情爆发开始至2020年5月15日的数据。欧洲的病死率最高(CFR,9.22%),而大洋洲从COVID-19中的康复率最高(91.15%)。在南亚国家中,印度的病例数最多(85,790例),其次是巴基斯坦(38,799例)和孟加拉国(20,065例)。然而,与其他地区相比,该地区进行的检测数量最少。在南亚国家中,印度的病死率最高(3.21%),而尼泊尔和不丹迄今为止尚无因COVID-19导致的死亡记录。康复率从马尔代夫的4.75%到斯里兰卡的51.02%不等。在孟加拉国,已记录到社区传播,达卡检测到的病例数最多,其次是纳拉扬甘杰和吉大港。我们将达卡及其周边六个区,即加济布尔、纳西迪、纳拉扬甘杰、蒙希甘杰、马尼甘杰和沙里亚特布尔,检测为基于99%置信度的热点地区,而法里德布尔和马达里布尔区为孟加拉国基于95%置信度的COVID-19空间热点地区。然而,我们在孟加拉国未发现任何冷点地区。我们在印度不同置信水平下确定了三个热点地区和三个冷点地区。本研究结果表明应采用“检测、追踪和隔离”方法尽早发现感染,以防止COVID-19进一步在社区传播。