ABSTRACT
Objective: Healthcare services using mobile-phone based telemedicine provide simple technology that does not require sophisticated equipment. This study assessed community health workers’ knowledge, attitude, and practice (i.e., their readiness) at the village level for uptake of mobile-phone based telemedicine.Materials and Methods: This cross-sectional study was conducted among 80 community health workers, including Auxiliary Nurse Midwives, Multipurpose Health Workers and Accredited Social Health Activists working in a rural health block of India. A pre-tested, semi-structured, interviewer-assisted, self-administered questionnaire was used to assess their mobile-phone based telemedicine readiness.Results: Sixty (75.0%) health workers owned mobile phones. The median readiness score for mobile-phone based telemedicine was 109.0. The Accredited Social Health Activists showed a better attitude toward mobile-phone based telemedicine than others. There was a significant moderate positive correlation (r=0.67) between knowledge and practice domains. Community health workers who had smartphones showed a significantly better attitude than those who did not.Conclusion: Training programs on telemedicine service delivery, focused on Auxiliary Nurse Midwives/ Multipurpose Health Workers, can improve their attitudes towards telemedicine. A better attitude of the Accredited Social Health Activists must be leveraged to initiate mobile-phone based telemedicine services on a pilot basis initially and later scaled up in other settings.
ABSTRACT
Objectives@#During the coronavirus disease 2019 (COVID-19) pandemic, countries around the world framed specific laws and imposed varying degrees of lockdowns to ensure the maintenance of physical distancing. Understanding changes in temporal and spatial mobility patterns may provide insights into the dynamics of this infectious disease. Therefore, we assessed the efficacy of lockdown measures in 16 countries worldwide by analyzing the relationship between community mobility patterns and the doubling time of COVID-19. @*Methods@#We performed a retrospective record-based analysis of population-level data on the doubling time for COVID-19 and community mobility. The doubling time for COVID-19 was calculated based on the laboratory-confirmed cases reported daily over the study period (from February 15 to May 2, 2020). Principal component analysis (PCA) of six mobility pattern-related variables was conducted. To explain the magnitude of the effect of mobility on the doubling time, a finite linear distributed lag model was fitted. The k-means clustering approach was employed to identify countries with similar patterns in the significant co-efficient of the mobility index, with the optimal number of clusters derived using Elbow’s method. @*Results@#The countries analyzed had reduced mobility in commercial and social places. Reduced mobility had a significant and favorable association with the doubling time of COVID-19—specifically, the greater the mobility reduction, the longer the time taken for the COVID-19 cases to double. @*Conclusions@#COVID-19 lockdowns achieved the immediate objective of mobility reduction in countries with a high burden of cases.