ABSTRACT
Diagnostic assays for various infectious diseases, including COVID-19, have been challenged for their utility as standalone point-of-care diagnostic tests due to suboptimal accuracy, complexity, high cost or long turnaround times for results. It is therefore critical to optimise their use to meet the needs of users. We used a simulation approach to estimate diagnostic outcomes, number of tests required and average turnaround time of using two-test algorithms compared with singular testing;the two tests were reverse transcription polymerase chain reaction (RT-PCR) and an antigen-based rapid diagnostic test (Ag-RDT). A web-based application of the model was developed to visualise and compare diagnostic outcomes for different disease prevalence and test performance characteristics (sensitivity and specificity). We tested the model using hypothetical prevalence data for COVID-19, representing low- and high-prevalence contexts and performance characteristics of RT-PCR and Ag-RDTs. The two-test algorithm when RT-PCR was applied to samples negative by Ag-RDT predicted gains in sensitivity of 27% and 7%, respectively, compared with Ag-RDT and RT-PCR alone. Similarly, when RT-PCR was applied to samples positive by Ag-RDT, specificity gains of 2.9% and 1.9%, respectively, were predicted. The algorithm using Ag-RDT followed by RT-PCR as a confirmatory test for positive patients limited the requirement of RT-PCR testing resources to 16,400 and 3,034 tests when testing a population of 100,000 with an infection prevalence of 20% and 0.05%, respectively. A two-test algorithm comprising a rapid screening test followed by confirmatory laboratory testing can reduce false positive rate, produce rapid results and conserve laboratory resources, but can lead to large number of missed cases in high prevalence setting. The web application of the model can identify the best testing strategies, tailored to specific use cases and we also present some examples how it was used as part of the Access to Covid-19 Tools (ACT) Accelerator Diagnostics Pillar.
ABSTRACT
Diagnostic assays for various infectious diseases, including COVID-19, have been challenged for their utility as standalone point-of-care diagnostic tests due to suboptimal accuracy, complexity, high cost or long turnaround times for results. It is therefore critical to optimise their use to meet the needs of users. We used a simulation approach to estimate diagnostic outcomes, number of tests required and average turnaround time of using two-test algorithms compared with singular testing; the two tests were reverse transcription polymerase chain reaction (RT-PCR) and an antigen-based rapid diagnostic test (Ag-RDT). A web-based application of the model was developed to visualise and compare diagnostic outcomes for different disease prevalence and test performance characteristics (sensitivity and specificity). We tested the model using hypothetical prevalence data for COVID-19, representing low- and high-prevalence contexts and performance characteristics of RT-PCR and Ag-RDTs. The two-test algorithm when RT-PCR was applied to samples negative by Ag-RDT predicted gains in sensitivity of 27% and 7%, respectively, compared with Ag-RDT and RT-PCR alone. Similarly, when RT-PCR was applied to samples positive by Ag-RDT, specificity gains of 2.9% and 1.9%, respectively, were predicted. The algorithm using Ag-RDT followed by RT-PCR as a confirmatory test for positive patients limited the requirement of RT-PCR testing resources to 16,400 and 3,034 tests when testing a population of 100,000 with an infection prevalence of 20% and 0.05%, respectively. A two-test algorithm comprising a rapid screening test followed by confirmatory laboratory testing can reduce false positive rate, produce rapid results and conserve laboratory resources, but can lead to large number of missed cases in high prevalence setting. The web application of the model can identify the best testing strategies, tailored to specific use cases and we also present some examples how it was used as part of the Access to Covid-19 Tools (ACT) Accelerator Diagnostics Pillar.
ABSTRACT
BACKGROUND: Rapidly growing coronavirus disease 2019 (COVID-19) pandemic has brought unprecedented challenges to the health system in Nepal. The main objective of this study was to explore the health system preparedness for COVID-19 and its impacts on frontline health-care workers in Nepal. METHODS: Semi-structured interviews were conducted among 32 health-care workers who were involved in clinical care of COVID-19 patients and four policy-makers who were responsible for COVID-19 control and management at central and provincial level. Interviews were conducted through telephone or Internet-based tools such as Zoom and Skype. All interviews were audio-recorded, transcribed into English, and coded using inductive and deductive approaches. RESULTS: Both health-care workers and policy-makers reported failure to initiate pre-emptive control measures at the early stages of the outbreak as the pivot in pandemic control. Although several measures were rolled out when cases started to appear, the overall health system preparedness was low. The poor governance, and coordination between three tiers of government was compounded by the inadequate personal protective equipment for health-care workers, insufficient isolation beds for patients, and poor engagement of the private sector. Frontline health-care workers experienced various degrees of stigma because of their profession and yet were able to maintain their motivation to continue serving patients. CONCLUSION: Preparedness for COVID-19 was affected by the poor coordination between three tiers of governance. Specifically, the lack of human resources, inadequate logistic chain management and laboratory facilities for testing COVID-19 appeared to have jeopardized the health system preparedness and escalated the pandemic in Nepal. Despite the poor preparedness, and health and safety concerns, health-care workers maintained their motivation. There is an urgent need for an effective coordination mechanism between various tiers of health structure (including private sector) in addition to incentivizing the health-care workers for the current and future pandemics.
ABSTRACT
BACKGROUND: In response to the COVID-19 pandemic, incoming travelers were quarantined at specific centers in Nepal and major checkpoints in Nepal-India border. Nepal adopted a generic public health approaches to control and quarantine returnee migrants, with little attention towards the quality of quarantine facilities and its aftermath, such as the poor mental health of the returnee migrants. The main objective of this study was to explore the status of anxiety and depression, and factors affecting them among returnee migrants living in institutional quarantine centers of western Nepal. METHODS: A mixed method approach in this study included a quantitative survey and in-depth interviews (IDIs) among respondents in quarantine centers of Karnali province between 21st April and 15th May 2020. Survey questionnaire utilized Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) tools, which were administered among 441 quarantined returnee migrants. IDIs were conducted among 12 participants which included a mix of six quarantined migrants and healthcare workers each from the quarantine centres. Descriptive and inferential analyses were conducted on quantitative data; and thematic analysis was utilized for qualitative data. RESULTS: Mild depression (9.1%; 40/441) and anxiety (16.1%; 71/441) was common among respondents followed by moderate depression and anxiety {depression (3.4%; 15/441), anxiety (4.1%; 18/441)} and severe depression and anxiety {depression (1.1%; 5/441), anxiety (0.7%; 3/441)}. Anxiety and depression were independent of their socio-demographic characteristics. Perceived fear of contracting COVID-19, severity and death were prominent among the respondents. Respondents experienced stigma and discrimination in addition to being at the risk of disease and possible loss of employment and financial responsibilities. In addition, poor (quality and access to) health services, and poor living condition at the quarantine centres adversely affected respondents' mental health. CONCLUSION: Depression and anxiety were high among quarantined population and warrants more research. Institutional quarantine centers of Karnali province of Nepal were in poor conditions which adversely impacted mental health of the respondents. Poor resource allocation for health, hygiene and living conditions can be counterproductive to the population quarantined.