The Impact of Human Mobility on Regional and Global Efforts to Control HIV Transmission

Eshraghian, Emily; Ferdos, Sepideh N; Mehta, Sanjay R.

doi:10.3390/v12010067

Cited by 16 publications

(11 citation statements)

References 52 publications

(69 reference statements)

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“…The mobility indicators depicted strong correlations with epidemiological characteristics for both the lockdown and unlock phases. This trend is consistent with many theoretical studies that have predicted the role of mobility for infectious diseases [ 10 , 52 , 53 ]. Previous studies have demonstrated the utility of mobility in the spread of COVID-19 data globally [ 31 , 54 ].…”

Section: Discussionsupporting

confidence: 92%

Exploring the Utility of Google Mobility Data During the COVID-19 Pandemic in India: Digital Epidemiological Analysis

Kishore¹,

Jaswal²,

Verma³

et al. 2021

JMIR Public Health Surveill

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Background Association between human mobility and disease transmission has been established for COVID-19, but quantifying the levels of mobility over large geographical areas is difficult. Google has released Community Mobility Reports (CMRs) containing data about the movement of people, collated from mobile devices. Objective The aim of this study is to explore the use of CMRs to assess the role of mobility in spreading COVID-19 infection in India. Methods In this ecological study, we analyzed CMRs to determine human mobility between March and October 2020. The data were compared for the phases before the lockdown (between March 14 and 25, 2020), during lockdown (March 25-June 7, 2020), and after the lockdown (June 8-October 15, 2020) with the reference periods (ie, January 3-February 6, 2020). Another data set depicting the burden of COVID-19 as per various disease severity indicators was derived from a crowdsourced API. The relationship between the two data sets was investigated using the Kendall tau correlation to depict the correlation between mobility and disease severity. Results At the national level, mobility decreased from –38% to –77% for all areas but residential (which showed an increase of 24.6%) during the lockdown compared to the reference period. At the beginning of the unlock phase, the state of Sikkim (minimum cases: 7) with a –60% reduction in mobility depicted more mobility compared to –82% in Maharashtra (maximum cases: 1.59 million). Residential mobility was negatively correlated (–0.05 to –0.91) with all other measures of mobility. The magnitude of the correlations for intramobility indicators was comparatively low for the lockdown phase (correlation ≥0.5 for 12 indicators) compared to the other phases (correlation ≥0.5 for 45 and 18 indicators in the prelockdown and unlock phases, respectively). A high correlation coefficient between epidemiological and mobility indicators was observed for the lockdown and unlock phases compared to the prelockdown phase. Conclusions Mobile-based open-source mobility data can be used to assess the effectiveness of social distancing in mitigating disease spread. CMR data depicted an association between mobility and disease severity, and we suggest using this technique to supplement future COVID-19 surveillance.

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Section: Discussionsupporting

confidence: 92%

Exploring the Utility of Google Mobility Data During the COVID-19 Pandemic in India: Digital Epidemiological Analysis

Kishore¹,

Jaswal²,

Verma³

et al. 2021

JMIR Public Health Surveill

View full text Add to dashboard Cite

show abstract

“…The mobility indicators depicted strong correlations with epidemiological characteristics for both the lockdown and unlock phases. This trend is consistent with many theoretical studies that have predicted the role of mobility for infectious diseases [10,52,53]. Previous studies have demonstrated the utility of mobility in the spread of COVID-19 data globally [31,54].…”

Section: Discussionsupporting

confidence: 90%

Exploring the Utility of Google Mobility Data During the COVID-19 Pandemic in India: Digital Epidemiological Analysis (Preprint)

Kishore¹,

Jaswal²,

Verma³

et al. 2021

Preprint

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BACKGROUND Association between human mobility and disease transmission for COVID-19 is established, but quantifying the levels of mobility over large geographical areas is difficult. Google released Community Mobility Report (CMR) data collated from mobile devices and gives an idea about the movement of people. OBJECTIVE Therefore, we attempt to explore the use of CMR to assess the role of mobility in spreading COVID-19 infection in India. METHODS An Ecological study analyzed CMR for human mobility. The data were compared for before, during, and after lockdown phases with the reference periods. Another dataset depicting the burden of COVID-19 after deriving various disease severity indicators was derived from a crowd-sourced Application Programming software. The relationship between the two datasets was investigated using Kendall’s tau correlation to depict the correlation between mobility and disease severity. RESULTS At the national level, mobility decreased everywhere except residential areas during the lockdown period, compared to the reference period. Mizoram (minimum cases) depicted a higher relative change in mobility than Maharashtra (maximum cases). Residential mobility negatively correlated with all other measures of mobility. The magnitude of correlations for intra-mobility indicators was comparatively low for the lockdown phase compared to other phases. A high correlation coefficient between epidemiological and mobility indicators is observed for the lockdown and unlock phases compared to the pre-lockdown. CONCLUSIONS We can use mobile-based open-source mobility data to provide the temporal anatomy of social distancing. CMR data depicted an association between mobility and disease severity, and we suggest that this technique supplement future COVID-19 surveillance. CLINICALTRIAL NA

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“…The massive local, regional, and international movement of people in a global world also presents a new challenge for humanity -the rapid and encompassing development of epidemics (Bajardi et al, 2011;Eshraghian et al, 2020). In just two months, SARS-CoV-2 spread across the world from the locus of origin in Wuhan (China) infecting approximately 5 million humans by May 20, 2020 (WHO.int).…”

Section: Introductionmentioning

confidence: 99%

COVID-19 pandemic and associated lockdown as a “Global Human Confinement Experiment” to investigate biodiversity conservation

Bates

Primack

Moraga

et al. 2020

Biological Conservation

224

200

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Efforts to curtail the spread of the novel coronavirus (SARS-CoV2) have led to the unprecedented concurrent confinement of nearly two-thirds of the global population. The large human lockdown and its eventual relaxation can be viewed as a Global Human Confinement Experiment. This experiment is a unique opportunity to identify positive and negative effects of human presence and mobility on a range of natural systems, including wildlife, and protected areas, and to study processes regulating biodiversity and ecosystems. We encourage ecologists, environmental scientists, and resource managers to contribute their observations to efforts aiming to build comprehensive global understanding based on multiple data streams, including anecdotal observations, systematic assessments and quantitative monitoring. We argue that the collective power of combining diverse data will transcend the limited value of the individual data sets and produce unexpected insights. We can also consider the confinement experiment as a "stress test" to evaluate the strengths and weaknesses in the adequacy of existing networks to detect human impacts on natural systems. Doing so will provide evidence for the value of the conservation strategies that are presently in place, and create future networks, observatories and policies that are more adept in protecting biological diversity across the world.

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The Impact of Human Mobility on Regional and Global Efforts to Control HIV Transmission

Cited by 16 publications

References 52 publications

Exploring the Utility of Google Mobility Data During the COVID-19 Pandemic in India: Digital Epidemiological Analysis

Exploring the Utility of Google Mobility Data During the COVID-19 Pandemic in India: Digital Epidemiological Analysis

Exploring the Utility of Google Mobility Data During the COVID-19 Pandemic in India: Digital Epidemiological Analysis (Preprint)

COVID-19 pandemic and associated lockdown as a “Global Human Confinement Experiment” to investigate biodiversity conservation

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