Dataset Information

The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology.

ABSTRACT: The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to support contact tracing efforts. While these data may be an important part of COVID-19 response, their use must be considered alongside a careful understanding of the behaviors and populations they capture. Here, we review the different applications for mobile phone data in guiding and evaluating COVID-19 response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data. We also discuss best practices and potential pitfalls for directly integrating the collection, analysis, and interpretation of these data into public health decision making.

SUBMITTER: Grantz KH

PROVIDER: S-EPMC7528106 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology.

Grantz Kyra H KH Meredith Hannah R HR Cummings Derek A T DAT Metcalf C Jessica E CJE Grenfell Bryan T BT Giles John R JR Mehta Shruti S Solomon Sunil S Labrique Alain A Kishore Nishant N Buckee Caroline O CO Wesolowski Amy A

Nature communications 20200930 1

The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to support contact tracing efforts. While these data may be an important part of COVID-19 response, their use must be considered alongside a careful understanding of the behaviors and populations they captu ...[more]

PMID: 32999287

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Project description:ObjectiveThe global health crisis in the form of COVID-19 has forced people to shift their routine activities into a remote environment with the help of technology. The outbreak of the COVID-19 has caused several organizations to be shut down and forced them to initiate work from home employing technology. Now more than ever, it's important for people and institutions to understand the impact of excessive use of mobile phone technology and electronic gadgets on human health, cognition, and behavior. It is important to understand their perspective and how individuals are coping with this challenge in the wake of the COVID-19 pandemic. The investigation is an effort to answer the research question: whether dependency on technology during lockdown has more effects on human health in comparison to normal times.MethodsThe study included participants from India (n = 122). A questionnaire was framed and the mode of conducting the survey chosen was online to maintain social distancing during the time of the Pandemic. The gathered data was statistically analysed employing RStudio and multiple regression techniques.ResultsThe statistical analysis confirms that lockdown scenarios have led to an increase in the usage of mobile phone technology which has been confirmed by around 90% of participants. Moreover, 95% of the participants perceive an increased risk of developing certain health problems due to excessive usage of mobile phones and technology. It has been evaluated that participants under the age group 15-30 years are highly affected (45.9%) during lockdown due to excessive dependence on technology. And, amongst different professions, participants involved in online teaching-learning are the most affected (42.6%).ConclusionThe findings indicate that dependency on technology during lockdown has more health effects as compared to normal times. So, it is suggested that as more waves of pandemics are being predicted, strategies should be planned to decrease the psychological and physiological effects of the overuse of technology during lockdown due to pandemics. As the lockdown situation unfolds, people and organization functioning styles should be rolled back to the limited dependency on technology.

Project description:The outbreak of coronavirus disease (COVID-19) has caused a significant public health challenge worldwide. A lack of effective methods for screening potential patients, rapidly diagnosing suspected cases, and accurately monitoring of the epidemic in real time to prevent the rapid spread of COVID-19 raises significant difficulties in mitigating the epidemic in many countries. As effective point-of-care diagnosis tools, simple, low-cost and rapid sensors have the potential to greatly accelerate the screening and diagnosis of suspected patients to improve their treatment and care. In particular, there is evidence that multiple pathogens have been detected in sewage, including SARS-CoV-2, providing significant opportunities for the development of advanced sensors for wastewater-based epidemiology that provide an early warning of the pandemic within the population. Sensors could be used to screen potential carriers, provide real-time monitoring and control of the epidemic, and even support targeted drug screening and delivery within the integration of emerging mobile health (mHealth) technology. In this communication, we discuss the feasibility of an integrated point-of-care biosensor system with mobile health for wastewater-based epidemiology (iBMW) for early warning of COVID-19, screening and diagnosis of potential infectors, and improving health care and public health. The iBMW will provide an effective approach to prevent, evaluate and intervene in a fast, affordable and reliable way, thus enabling real-time guidance for the government in providing effective intervention and evaluating the effectiveness of intervention. Highlights • Point-of-care biosensors for rapid and reliable COVID-19 diagnosis.• Community sewage sensors for tracing and early warning of COVID-19 within population.• Point-of-use sensor-based mHealth for health care and epidemic management and intervention.• Microfluidics for effective drug delivery for potential therapy of COVID-19.

Dataset Information

The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology.

Publications

The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology.

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