Data analytics and knowledge management approach for COVID-19 prediction and control.

The Coronavirus Disease (COVID-19) caused by SARS-CoV-2, continues to be a global threat. The major global concern among scientists and researchers is to develop innovative digital solutions for prediction and control of infection and to discover drugs for its cure. In this paper we developed a strategic technical solution for surveillance and control of COVID-19 in Delhi-National Capital Region (NCR). This work aims to elucidate the Delhi COVID-19 Data Management Framework, the backend mechanism of integrated Command and Control Center (iCCC) with plugged-in modules for various administrative, medical and field operations. Based on the time-series data extracted from iCCC repository, the forecasting of COVID-19 spread has been carried out for Delhi using the Auto-Regressive Integrated Moving Average (ARIMA) model as it can effectively predict the logistics requirements, active cases, positive patients, and death rate. The intelligence generated through this research has paved the way for the Government of National Capital Territory Delhi to strategize COVID-19 related policies formulation and implementation on real time basis. The outcome of this innovative work has led to the drastic reduction in COVID-19 positive cases and deaths in Delhi-NCR.

Parental experience of an early developmental surveillance programme for autism within Australian general practice: a qualitative study.

OBJECTIVES: Implementing support and services early in the life course has been shown to promote positive developmental outcomes for children at high likelihood of developmental conditions including autism. This study examined parents'/caregivers' experiences and perceptions about a digital developmental surveillance pathway for autism, the autism surveillance pathway (ASP), and usual care, the surveillance as usual (SaU) pathway, in the primary healthcare general practice setting. DESIGN: This qualitative study involves using a convenience selection process of the full sample of parents/caregivers that participated in the main programme, 'General Practice Surveillance for Autism', a cluster-randomised controlled trial study. All interviews were audio-recorded, transcribed and coded using NVivo V.12 software. An inductive thematic interpretive approach was adopted and data were analysed thematically. PARTICIPANTS: Twelve parents/caregivers of children with or without a developmental condition/autism (who participated in the main programme) in South Western Sydney and Melbourne were interviewed. SETTINGS: All interviews were completed over the phone. RESULTS: There were seven major themes and 20 subthemes that included positive experiences, such as pre-existing patient-doctor relationships and their perceptions on the importance of knowing and accessing early support/services. Barriers or challenges experienced while using the SaU pathway included long waiting periods, poor communication and lack of action plans, complexity associated with navigating the healthcare system and lack of understanding by general practitioners (GPs). Common suggestions for improvement included greater awareness/education for parents/carers and the availability of accessible resources on child development for parents/caregivers. CONCLUSION: The findings support the use of digital screening tools for developmental surveillance, including for autism, using opportunistic contacts in the general practice setting. TRIAL REGISTRATION NUMBER: ANZCTR (ACTRN12619001200178).

iQMS: IoT-based QMS framework for tracking of quarantined subjects.

The outbreak of Coronavirus Disease as a pandemic has resulted in a huge saddle on health infrastructure. Preventive measures such as quarantine, social distancing, isolation, and community containment play a pivotal role to contain the spread of exponentially growing COVID cases. This huge burden permitted authorities for institutional/home quarantine for the suspected persons. The biggest challenge for institutional/home quarantine is to monitor and track the movement of quarantined persons. These suspected cases pose a serious threat in outbreak and transmission of the disease. In this paper, an intelligent-Quarantine Monitoring System (iQMS) has been presented which comprises of a wearable IoT-based wristband, bundled with an android mobile app to track and report the absconding quarantined subjects in near real-time. The iQMS incorporates a cloud-based solution with IoT sensors using a global positioning system (GPS) based tracker for geo-fencing breach. The proposed system will facilitate the authorities in remote monitoring and tracking of identified subjects.