Background: Geographic information science (GIS) has established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in COVID-related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools in the COVID-19 pandemic. Methods: We systematically retrieved and reviewed 79 research articles that either directly used GIS or other geospatial tools as part of their analysis. We grouped the identified papers under six broader thematic groups based on the objectives and research questions of the study- environmental, socio-economic, and cultural, public health, spatial transmission, computer-aided modeling, and data mining. Results: The interdisciplinary nature of how geographic and spatial analysis was used in COVID-19 research was notable among the reviewed papers. Although GIS has substantial potential in planning to slow down the spread, surveillance, contact tracing, and identify the trends and hotspots of breakdowns, it was not employed as much as it could have been. This review not only provided an overarching view on how GIS has been used in COVID-19 research so far but also concluded that this geospatial analysis and technologies could be used in future public health emergencies along with statistical and other socio-economic modeling techniques. Our systematic review also provides how both scientific communities and policymakers could leverage GIS to extract useful information to make an informed decision in the future. Conclusions:  Despite the limited applications of GIS in identifying the nature and spatio-temporal pattern of this raging pandemic, there are opportunities to utilize these techniques in handling the pandemic. The use of spatial analysis and GIS could significantly improve how we understand the pandemic as well as address the underserviced demographic groups and communities.

Geographic Information Science (GIS) had established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in the COVID related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools and technologies in COVID-19 pandemic. We systematically retrieved and reviewed 79 research articles that either directly used GIS or other Geospatial tools as part of their analysis. We grouped the identified papers under six broader thematic groups based on the objectives and research questions of the study- environmental, socio-economic, and cultural, public health, spatial transmission, computer-aided modeling, and data mining. The interdisciplinary nature of how geographic and spatial analysis was used in COVID-19 research was noticeable among the reviewed papers. Although GIS has substantial potential in planning to slow down the spread, surveillance, contact tracing, and identify the trends and hotspots of breakdowns, it was not employed as much as it could have been. This review not only provided an overarching view on how GIS has been used in COVID-19 research so far but also concluded that this geospatial analysis and technologies could be used in future public health emergencies along with statistical and other socio-economic modeling techniques. Our systematic review also provides how both scientific communities and policymakers could leverage GIS to extract useful information to make an informed decision in the coming days.

Background: Geographic information science (GIS) has established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in COVID-related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools in the COVID-19 pandemic. Methods: We systematically retrieved and reviewed 79 research articles that either directly used GIS or other geospatial tools as part of their analysis. We grouped the identified papers under six broader thematic groups based on the objectives and research questions of the study- environmental, socio-economic, and cultural, public health, spatial transmission, computer-aided modeling, and data mining. Results: The interdisciplinary nature of how geographic and spatial analysis was used in COVID-19 research was notable among the reviewed papers. Geospatial techniques, especially WebGIS, have even been widely used to visualize the data on a map and were critical to informing the public regarding the spread of the virus, especially during the early days of the pandemic. This review not only provided an overarching view on how GIS has been used in COVID-19 research so far but also concluded that geospatial analysis and technologies could be used in future public health emergencies along with statistical and other socio-economic modeling techniques. Our review also highlighted how scientific communities and policymakers could leverage GIS to extract useful information to make an informed decision in the future. Conclusions:  Despite the limited applications of GIS in identifying the nature and spatio-temporal pattern of this raging pandemic, there are opportunities to utilize these techniques in handling the pandemic. The use of spatial analysis and GIS could significantly improve how we understand the pandemic as well as address the underserviced demographic groups and communities.

In May 2020, when Bangladesh was struggling with community transmission of COVID-19, the country had to face the strongest tropical storm-Cyclone Amphan -which puts the evacuation process in jeopardy. Thus, it is crucial to measure the public risk perception about COVID-19 and its influence on the evacuation decision. This study explores the nexus between COVID-19 risk perception and coastal peoples' evacuation decisions during cyclone Amphan. With an analysis of 378 sample households survey data of the Satkhira district, this study developed the COVID-19 risk perception index using Principal Component Analysis (PCA) and categorized the respondents based on the score. The result shows that 1.85 %, 21.43 %, 45.77 %, 25.13 %, and 5.82 % have very low, low, moderate, high, and very high-risk perceptions, respectively. The analysis also reveals that 96.6 % of the respondents received an evacuation order during Amphan, but only 42 % complied with the order. The t-test analysis and common language effect size test of the survey data reveal that the respondents with a high perception score are 65 % less likely to evacuate than the respondents with low perception scores. This study has important implications in guiding concerned authorities to combat natural disasters during COVID-19 and other similar public health emergencies in the future.

Cyclone Amphan battered the coastal communities in the southwestern part of Bangladesh in 2020 during the COVID-19 pandemic. These coastal communities were experiencing such a situation for the first time and faced the dilemma of whether to stay at home and embrace the cyclone or be exposed to the COVID-19 virus in the cyclone shelters by evacuating. This article intends to explore individuals’ decisions regarding whether to evacuate in response to cyclone Amphan and in light of the risks of the COVID-19 pandemic. Consequently, this study investigated evacuation behaviors among the households and explored the impacts of COVID-19 during the evacuation procedures. We conducted household surveys to collect primary information and undertook 378 samples for interviews at a precision level of 0.05 in fourteen villages. Despite the utmost effort of the government, the results demonstrated that 96.6% of people in the coastal area received a cyclone evacuation order before the cyclone’s landfall, and only 42% of people followed the evacuation order. The majority of households chose to stay at home because of fear of COVID-19 exposure in the crowded shelters. Although half of the evacuees were housed in cyclone shelters, COVID-19 preventive measures were apparently not set in place. Thus, this study will assist in crafting future government policies to enhance disaster evacuation plans by providing insights from the pandemic that can inform disaster management plans in the Global South.