Write an essay on 'Importance of mobiles for students during the COVID-19 pandemic' exceeding 250 words.
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The coronavirus disease 2019 (COVID-19) pandemic caused by the novel coronavirus (SARS-CoV-2) has created an unprecedented challenge for governments, public health agencies, medical officials, and populations globally1,2. The public health response is seeking to effectively mitigate and contain the pandemic while balancing social and economic costs3,4,5. Control strategies thus far have primarily consisted of non-pharmaceutical interventions (NPIs), which have slowed down the epidemic in many settings. Most NPIs rely on reducing contact between infected and susceptible individuals through mass social distancing, including restrictions on social gatherings, closures of schools and businesses, shelter-in-place or stay-at-home orders or lockdowns, travel restrictions, active monitoring, and increased testing, contact tracing, and isolation measures6,7,8,9. These interventions are effective when they result in large-scale human behavioral changes that reduce the close contacts and mobility patterns that facilitate disease transmission, but are challenging to maintain10. Quantifying these patterns to assess NPI effectiveness, particularly on the spatial, temporal, and population scales necessary to fully inform public health response, is an important challenge for this pandemic response.
As a result of the rapid spread and grievous toll exacted by the COVID-19 pandemic, there has been increasing interest in developing innovative methods and tools to inform public health response through digital data, including mobile phone data both passively collected by mobile phone operators and actively collected via recently developed applications11. Mobile phone data remain one of the best sources of information on large-scale population behaviors12. These data can be collected in high- and low-income settings and can capture, in near real-time, changes in mobility and clustering patterns for large swaths of the population. We and others have previously used aggregated and anonymized geolocation information from passively collected mobile phone data to successfully inform and model the spatial and temporal dynamics of endemic and emerging infectious diseases, including malaria13,14,15,16, cholera17, measles18,19,20,21,22,23, dengue24,25, and Ebola26,27. Through these prior applications, an understanding of privacy-conscious ways to utilize these data and inform public health policy while forming productive collaborations with operators, public health officials, and academic partners has been developed.
Mobility analysis, quantifying clustering of social contacts, symptom tracking, surveying, and contact tracing applications have all been proposed and employed to some degree to inform the response to COVID-19 (see Fig. 1a). These applications, metrics developed to analyze these data, and proposed best practices have recently been reviewed by an interdisciplinary team of experts28. To build on this work, we examine the applicability of mobile phone data for public health response by reviewing the common applications of mobile phone data relevant to outbreak response; the kinds of behaviors captured within these data and proposed applications; the validity of these data for public health response and epidemiologic research, including sources and implications of selection bias; and potential concerns and best practices for direct integration of these data with public health response.