ABSTRACT
Introduction/ Background: Rapid, scalable point-of-care COVID-19 testing at community-level may hold the key towards diagnosis and control in resource-limited settings. Our initial door-to-door symptom-based strategy yielded low COVID-19 cases. We therefore investigated COVID19 case detection using a strategy of community hubs in a peri-urban community (~27,000) with high TB/HIV prevalence in Zambia. Methods: COVID19 screening was delivered using “community hubs”, walk-in testing locations staffed by 2 Community Health Workers serving 3000 to 4000 people. Between May-October 2021 4 hubs were operated in high-risk transmission hotspots changing location weekly. All persons attending the hubs were offered COVID-19 testing (Panbio-AgRDT and a PCR (Cepheid-Xpert-Xpress TM or VitaPCRTM RT-PCR assay (Credo Diagnostics Biomedical, Singapore), depending on availability) and symptoms screening;TB/HIV screening and testing;counselling and linkage to routine care. Qualitative methods included: mystery shoppers, focus group discussions with different groups and observations. Results: Over 6 months, 2956 people were screened at the hubs, 1724 (58%) males with median age 30 years. Prevalence of COVID19 suggestive symptoms was 18.3% (540/2956). A total of 2938 antigen tests were done and 168 (5.7%) were positive. For PCR testing, by Xpert Xpress 370/1270 (29.1%) were positive and 113/951 (11.9%) by VitaPCR;157 (5.3%) were positive on both. Test positivity was strongly associated with being symptomatic (p<0.001). Antigen test positivity rate was 1.6% in asymptomatic versus 24.2% in symptomatic;for Xpert-Xpress 20.6% versus 46.5% and for Vita PCR 4.2% versus 30.4% respectively. Qualitative results are available. Impact: This study aims to generate and evaluate models of community-based COVID-19 services to improve the trace-screen-test- isolate cascade and management by overcoming barriers, reducing stigma, and enabling communities to access rapid-testing. Rapid dissemination of key findings will mitigate the impact of the SARS-CoV2 epidemic and to help increase the knowledge. Conclusion: Delivering COVID-19 case-finding using mobile community hubs is feasible and acceptable and contributed towards the district and national COVID19 response in Zambia. Symptomatic persons have a significant higher chance of being detected with SARS-COV-2.
ABSTRACT
Background and Aim: COVID-19 is a highly contagious infectious disease, and it has affected people's daily life and has raised great concern for governments and public health officials. Forecasting its future behavior may be useful for allocating medical resources and defining effective strategies for disease control, etc. Materials and Methods: The collected data was the cumulative and the absolute number of confirmed, death, and recovered cases of COVID-19 from February 20 to July 03, 2021. We used hierarchical cluster analysis. To forecast the future behavior of COVID-19, the Auto-Regressive Integrated Moving Average (ARIMA), Exponential Smoothing (ETS), Automatic Forecasting Procedure (Prophet), Naive, Seasonal Naive (s-Naive), boosted ARIMA, and boosted Prophet models were used. Results: The results of clustering showed a similar behavior of coronavirus in Iran and other countries such as France, Russia, Turkey, United Kingdom (UK), Argentina, Colombia, Italy, Spain, Germany, Poland, Mexico, and Indonesia. It also revealed similar patterns of SARS-CoV-2 for the same countries in six groups. Results showed that XGBoost models' family had higher accuracy than other models. Conclusion: In Iran, COVID-19 showed similar behavior patterns compared to the studied developed countries. The family of XGBoost models showed practical results and high precision in forecasting behavior patterns of the virus. Concerning the rapid spread of the virus worldwide, these models can be used to forecast the behavior patterns of SARS-CoV-2. Preventing the spread of the coronavirus, controlling the disease, and breaking down its chain necessitates community assistance, and in this mission, the role of statisticians cannot be neglected.
ABSTRACT
Exposure setting is crucial in the formation and propagation of SARS-CoV-2 transmission clusters. In this cohort study, transmission networks of 2 waves were differentiated by exposure setting using territory-wide surveillance data with clinical and laboratory records in Hong Kong. Characteristically, the first wave had resulted from imported cases followed by local transmissions, while the second wave was constituted primarily by local infections. With a 4-fold higher caseload, the second wave featured predominance of epidemiologically linked, local, older and asymptomatic patients with higher viral loads and shorter inpatient days. The 1028 transmission clusters formed 155 cascades composing at least two clusters. Daily and social activities were exposure settings that bridged clusters while residences usually terminated transmission cascades. Regulatory restrictions on social activities extinguished cluster formation in bars, but shifted to private parties in the second wave. The results confirmed that strategic interventions targeting exposure settings could achieve effective epidemic control.