Implementation of a COVID-19 Screening Testing Program in a Rural, Tribal Nation: Experience of the San Carlos Apache Tribe, January–February 2021

The COVID-19 pandemic has disproportionately affected tribal populations, including the San Carlos Apache Tribe. Universal screening testing in a community using rapid antigen tests could allow for near–real-time identification of COVID-19 cases and result in reduced SARS-CoV-2 transmission. Published experiences of such testing strategies in tribal communities are lacking. Accordingly, tribal partners, with support from the Centers for Disease Control and Prevention, implemented a serial testing program using the Abbott BinaxNOW rapid antigen test in 2 tribal casinos and 1 detention center on the San Carlos Apache Indian Reservation for a 4-week pilot period from January to February 2021. Staff members at each setting, and incarcerated adults at the detention center, were tested every 3 or 4 days with BinaxNOW. During the 4-week period, 3834 tests were performed among 716 participants at the sites. Lessons learned from implementing this program included demonstrating (1) the plausibility of screening testing programs in casino and prison settings, (2) the utility of training non–laboratory personnel in rapid testing protocols that allow task shifting and reduce the workload on public health employees and laboratory staff, (3) the importance of building and strengthening partnerships with representatives from the community and public and private sectors, and (4) the need to implement systems that ensure confidentiality of test results and promote compliance among participants. Our experience and the lessons learned demonstrate that a serial rapid antigen testing strategy may be useful in work settings during the COVID-19 pandemic as schools and businesses are open for service.

Use of standard samples for qualification inspections of testing laboratory for analysis safety of meat and meat products

This article provides insights into qualification testing, interlaboratory comparative testing, and qualification testing programs in testing laboratories that analyze the safety of meat and meat products. Samples with codes OK-MB- 21 were used as a model for interlaboratory comparisons. The uniformity and stability of the CC code was assessed in accordance with GOST R 50779.60-2017 “Statistical methods. Application in proficiency testing through interlaboratory testing ”. Seven laboratories participated in the proficiency testing program. The test preparation procedure was described and the test results determined whether each sample tested was satisfactory or questionable. Participants with unsatisfactory results are encouraged to identify the causes of the alarms, take corrective actions and document them, and identify and eliminate the causes of the unsatisfactory results.

ANALYSIS OF THE EFFECT OF FIXED ASSETS ON THE STOCK PRICE OF THE COMPANY INDEXED LQ45 ON THE INDONESIA STOCK EXCHANGE

The purpose of this research is to examine the effect of fixed assets and the impact of these variables on stock prices. The population used are companies that are included in the LQ45 index contained in the IDX with a period of 3 years (2018-2020). The number of samples used were 15 companies and used a purposive sampling method using the SSPS (Statistical Package for Social Science) program testing program. The results of this study are fixed assets in the company have a positive effect on shares.

Using mobile phone data to estimate dynamic population changes and improve the understanding of a pandemic: A case study in Andorra

Compartmental models are often used to understand and predict the progression of an infectious disease such as COVID-19. The most basic of these models consider the total population of a region to be closed. Many incorporate human mobility into their transmission dynamics, usually based on static and aggregated data. However, mobility can change dramatically during a global pandemic as seen with COVID-19, making static data unsuitable. Recently, large mobility datasets derived from mobile devices have been used, along with COVID-19 infections data, to better understand the relationship between mobility and COVID-19. However, studies to date have relied on data that represent only a fraction of their target populations, and the data from mobile devices have been used for measuring mobility within the study region, without considering changes to the population as people enter and leave the region. This work presents a unique case study in Andorra, with comprehensive datasets that include telecoms data covering 100% of mobile subscribers in the country, and results from a serology testing program that more than 90% of the population voluntarily participated in. We use the telecoms data to both measure mobility within the country and to provide a real-time census of people entering, leaving and remaining in the country. We develop multiple SEIR (compartmental) models parameterized on these metrics and show how dynamic population metrics can improve the models. We find that total daily trips did not have predictive value in the SEIR models while country entrances did. As a secondary contribution of this work, we show how Andorra's serology testing program was likely impacted by people leaving the country. Overall, this case study suggests how using mobile phone data to measure dynamic population changes could improve studies that rely on more commonly used mobility metrics and the overall understanding of a pandemic.

Rostered Routine Testing – A Necessary Evil?

We report our institution’s experience of detecting a staff who was infected with SARS-CoV-2 while he was asymptomatic as part of a rostered routine testing program, and how the institution was able to undertake measures to curb the spread hence reducing the impact on the daily operations of our institution.