Evaluating the Effectiveness of Interventions to Improve the Follow-up Rate for Children With Visual Disabilities in an Eye Hospital in Nepal: Nonrandomized Study.

BACKGROUND: Monitoring ocular morbidity among pediatric patients requires regular follow-up visits. We found that the follow-up rate was poor among children in our setting. Therefore, we intended to assess the effectiveness of 2 interventions-(1) counseling and (2) SMS text messaging and phone calls-to improve the follow-up rates. OBJECTIVE: This study aimed to evaluate the effectiveness of 2 interventions, counseling and SMS and phone calls group, as well as a routine standard care for improving the follow-up rate of pediatric patients. METHODS: A Nonrandomized, quasiexperimental design was used. Children (aged 0-16 years) with ocular conditions requiring at least 3 follow-up visits during the study period were included. A total of 264 participants were equally allocated to the 3 intervention groups of (1) counseling, (2) SMS and phone calls, and (3) routine standard care group. A 20-minute counseling session by a trained counselor with the provision of disease-specific leaflets were given to those in the counseling group. For the second intervention group, parents of children received an SMS text 3 days before and a phone call 1 day before their scheduled follow-up visits. Participants allocated for the routine standard care group were provided with the existing services with no additional counseling and reminders. Participants attending 3 follow-ups within 2 days of the scheduled visit date were considered compliant. The difference in and among the proportion of participants completing all 3 follow-up visits in each group was assessed. RESULTS: The demographic characteristics of the participants were similar across the study groups. Only 3% (8/264) of participants completed all 3 follow-up visits, but overall compliance with the follow-up, as defined by the investigators, was found to be only 0.76% (2/264). There was no statistically significant difference in the proportion of follow-up between the intervention groups. However, the proportion of participants attending the first and second follow-ups, as well as the overall total number of follow-ups, was more in the SMS and phone-call group followed by the counseling group. CONCLUSIONS: We did not find any evidence on the effectiveness of our interventions to improve the follow-up rate. The primary reason could be that this study was conducted during the COVID-19 pandemic. It could also be possible that the intensity of the interventions may have influenced the outcomes. A rigorously designed study during the absence of any lockdown restrictions is warranted to evaluate intervention effectiveness. The study also provides useful insights and highlights the importance of designing and systematically developing interventions for improving the follow-up rate and ensuring a continuum of care to children with visual disabilities in Nepal and similar contexts. TRIAL REGISTRATION: ClinicalTrials.gov NCT04837534; https://clinicaltrials.gov/ct2/show/NCT04837534. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/31578.

Chapter 6 - Modeling of COVID-19 Outbreak in Reference to Physical Parameters

The spread of coronavirus disease 2019 (COVID-19) in various countries varies in different manners, depending on the demographic and climatic conditions. This needs expediting better strategies to combat the novel coronavirus and also the emergence of new viral strains in the future. Our in-depth analysis suggests the spread of COVID-19 cases worldwide, the timeline of spread among most affected countries as of September 3, 2020. Evaluation of the climatic conditions in 2-week interval is carried out. The study recorded most of the countries getting affected by COVID-19 belong to the range of 25–35°C maximum temperature, 20–30°C minimum temperature, and 60%–80% relative humidity. To get a more generalized view on the spread, the study explored the temperature distribution of affected countries and chronicled in both minimum and maximum temperatures so that the number of COVID-19 cases mostly follows a lognormal distribution. In different ranges of relative humidity, not a single distribution is obtained to explain the spread of COVID-19 cases worldwide. A comparison between theoretic and descriptive parameters is also done to support the spread of COVID-19.

Study of the trend pattern of COVID-19 using spline-based time series model: a Bayesian paradigm.

A vast majority of the countries are under economic and health crises due to the current epidemic of coronavirus disease 2019 (COVID-19). The present study analyzes the COVID-19 using time series, an essential gizmo for knowing the enlargement of infection and its changing behavior, especially the trending model. We consider an autoregressive model with a non-linear time trend component that approximately converts into the linear trend using the spline function. The spline function splits the series of COVID-19 into different piecewise segments between respective knots in the form of various growth stages and fits the linear time trend. First, we obtain the number of knots with their locations in the COVID-19 series to identify the transmission stages of COVID-19 infection. Then, the estimation of the model parameters is obtained under the Bayesian setup for the best-fitted model. The results advocate that the proposed model appropriately determines the location of knots based on different transmission stages and know the current transmission situation of the COVID-19 pandemic in a country.