A Systematic Review of Smartphone Applications Available for Corona Virus Disease 2019 (COVID19) and the Assessment of their Quality Using the Mobile Application Rating Scale (MARS)

Davalbhakta, Samira; Advani, Shailesh; Kumar, Shobhit; Agarwal, Vishwesh; Bhoyar, Samruddhi; Fedirko, Elizabeth; Misra, Durga Prasanna; Goel, Ashish; Gupta, Latika; Agarwal, Vikas

doi:10.1007/s10916-020-01633-3

Cited by 168 publications

(153 citation statements)

References 17 publications

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“…To overcome these limitations, use of both spatial and temporally structured data has been proposed [ 35 ]. The use of contact tracing applications that provide anonymized geolocated data and serial interval estimates could provide more timely and robust epidemiological understanding of emerging diseases such as COVID-19 [ 36 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

Transmission Dynamics of the COVID-19 Epidemic at the District Level in India: Prospective Observational Study

Saurabh¹,

Verma²,

Gautam³

et al. 2020

JMIR Public Health Surveill

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Background On March 9, 2020, the first COVID-19 case was reported in Jodhpur, Rajasthan, in the northwestern part of India. Understanding the epidemiology of COVID-19 at a local level is becoming increasingly important to guide measures to control the pandemic. Objective The aim of this study was to estimate the serial interval and basic reproduction number (R0) to understand the transmission dynamics of the COVID-19 outbreak at a district level. We used standard mathematical modeling approaches to assess the utility of these factors in determining the effectiveness of COVID-19 responses and projecting the size of the epidemic. Methods Contact tracing of individuals infected with SARS-CoV-2 was performed to obtain the serial intervals. The median and 95th percentile values of the SARS-CoV-2 serial interval were obtained from the best fits with the weibull, log-normal, log-logistic, gamma, and generalized gamma distributions. Aggregate and instantaneous R0 values were derived with different methods using the EarlyR and EpiEstim packages in R software. Results The median and 95th percentile values of the serial interval were 5.23 days (95% CI 4.72-5.79) and 13.20 days (95% CI 10.90-18.18), respectively. R0 during the first 30 days of the outbreak was 1.62 (95% CI 1.07-2.17), which subsequently decreased to 1.15 (95% CI 1.09-1.21). The peak instantaneous R0 values obtained using a Poisson process developed by Jombert et al were 6.53 (95% CI 2.12-13.38) and 3.43 (95% CI 1.71-5.74) for sliding time windows of 7 and 14 days, respectively. The peak R0 values obtained using the method by Wallinga and Teunis were 2.96 (95% CI 2.52-3.36) and 2.92 (95% CI 2.65-3.22) for sliding time windows of 7 and 14 days, respectively. R0 values of 1.21 (95% CI 1.09-1.34) and 1.12 (95% CI 1.03-1.21) for the 7- and 14-day sliding time windows, respectively, were obtained on July 6, 2020, using method by Jombert et al. Using the method by Wallinga and Teunis, values of 0.32 (95% CI 0.27-0.36) and 0.61 (95% CI 0.58-0.63) were obtained for the 7- and 14-day sliding time windows, respectively. The projection of cases over the next month was 2131 (95% CI 1799-2462). Reductions of transmission by 25% and 50% corresponding to reasonable and aggressive control measures could lead to 58.7% and 84.0% reductions in epidemic size, respectively. Conclusions The projected transmission reductions indicate that strengthening control measures could lead to proportionate reductions of the size of the COVID-19 epidemic. Time-dependent instantaneous R0 estimation based on the process by Jombart et al was found to be better suited for guiding COVID-19 response at the district level than overall R0 or instantaneous R0 estimation by the Wallinga and Teunis method. A data-driven approach at the local level is proposed to be useful in guiding public health strategy and surge capacity planning.

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Section: Discussionmentioning

confidence: 99%

Transmission Dynamics of the COVID-19 Epidemic at the District Level in India: Prospective Observational Study

Saurabh¹,

Verma²,

Gautam³

et al. 2020

JMIR Public Health Surveill

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“…The public mandate to download the app as well as it's requirements such as continuous turned-on Bluetooth and location tracking has raised concerns in the Indian population. 29 Under the Disaster Management Act, which enables Indian states to act “as necessary,” concerns were raised on the disruption of privacy obligations, leading to stigmatization from neighbours and employers, without any solution to these patients. On the other side, there is no specific time limit for personal information being exposed while using social media.…”

Section: Operational Challenges Against Ethicsmentioning

confidence: 99%

Informed Consent for Scholarly Articles during the COVID-19 Pandemic

Jones¹,

Zimba

Gupta

2021

J Korean Med Sci

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“…However, only few applications have overlapping functions such as symptoms checker, contact tracing, and information dissemination functions. According to one study, in order to encourage wide use of a mobile application, it has to feature several important functions that are consolidated into a single system [5].…”

Section: Use Of Mobile Application To Contain Covid-19mentioning

confidence: 99%