Do not forget the children: a model-based analysis on the potential impact of COVID-19-associated interruptions in paediatric HIV prevention and care.

INTRODUCTION: The COVID-19 pandemic has affected women and children globally, disrupting antiretroviral therapy (ART) services and exacerbating pre-existing barriers to care for both pregnant women and paediatric populations. METHODS: We used the Spectrum modelling package and the CEPAC-Pediatric model to project the impact of COVID-19-associated care disruptions on three key populations in the 21 Global Plan priority countries in sub-Saharan Africa: (1) pregnant and breastfeeding women living with HIV and their children, (2) all children (aged 0-14 years) living with HIV (CLWH), regardless of their engagement in care and (3) CLWH who were engaged in care and on ART prior to the start of the pandemic. We projected clinical outcomes over the 12-month period of 1 March 2020 to 1 March 2021. RESULTS: Compared to a scenario with no care disruption, in a 3-month lockdown with complete service disruption, followed by 3 additional months of partial (50%) service disruption, a projected 755,400 women would have received PMTCT care (a 21% decrease), 187,800 new paediatric HIV infections would have occurred (a 77% increase) and 516,800 children would have received ART (a 35% decrease). For children on ART as of March 2020, we projected 507,200 would have experienced ART failure (an 80% increase). Additionally, a projected 88,400 AIDS-related deaths would have occurred (a 27% increase) between March 2020 and March 2021, with 51,700 of those deaths occurring among children engaged in care as of March 2020 (a 54% increase). CONCLUSIONS: While efforts will continue to curb morbidity and mortality stemming directly from COVID-19 itself, it is critical that providers also consider the immediate and indirect harms of this pandemic, particularly among vulnerable populations. Well-informed, timely action is critical to meet the health needs of pregnant women and children if the global community is to maintain momentum towards an AIDS-free generation.

Coronavirus Disease 2019 (COVID-19) Diagnostic Clinical Decision Support: A Pre-Post Implementation Study of CORAL (COvid Risk cALculator).

BACKGROUND: Isolation of hospitalized persons under investigation (PUIs) for coronavirus disease 2019 (COVID-19) reduces nosocomial transmission risk. Efficient evaluation of PUIs is needed to preserve scarce healthcare resources. We describe the development, implementation, and outcomes of an inpatient diagnostic algorithm and clinical decision support system (CDSS) to evaluate PUIs. METHODS: We conducted a pre-post study of CORAL (COvid Risk cALculator), a CDSS that guides frontline clinicians through a risk-stratified COVID-19 diagnostic workup, removes transmission-based precautions when workup is complete and negative, and triages complex cases to infectious diseases (ID) physician review. Before CORAL, ID physicians reviewed all PUI records to guide workup and precautions. After CORAL, frontline clinicians evaluated PUIs directly using CORAL. We compared pre- and post-CORAL frequency of repeated severe acute respiratory syndrome coronavirus 2 nucleic acid amplification tests (NAATs), time from NAAT result to PUI status discontinuation, total duration of PUI status, and ID physician work hours, using linear and logistic regression, adjusted for COVID-19 incidence. RESULTS: Fewer PUIs underwent repeated testing after an initial negative NAAT after CORAL than before CORAL (54% vs 67%, respectively; adjusted odd ratio, 0.53 [95% confidence interval, .44-.63]; P < .01). CORAL significantly reduced average time to PUI status discontinuation (adjusted difference [standard error], -7.4 [0.8] hours per patient), total duration of PUI status (-19.5 [1.9] hours per patient), and average ID physician work-hours (-57.4 [2.0] hours per day) (all P < .01). No patients had a positive NAAT result within 7 days after discontinuation of precautions via CORAL. CONCLUSIONS: CORAL is an efficient and effective CDSS to guide frontline clinicians through the diagnostic evaluation of PUIs and safe discontinuation of precautions.

Cost-effectiveness of public health strategies for COVID-19 epidemic control in South Africa

Background Healthcare resource constraints in low and middle-income countries necessitate selection of cost-effective public health interventions to address COVID-19. Methods We developed a dynamic COVID-19 microsimulation model to evaluate clinical and economic outcomes and cost-effectiveness of epidemic control strategies in KwaZulu-Natal, South Africa. Interventions assessed were Healthcare Testing (HT), where diagnostic testing is performed only for those presenting to healthcare centres;Contact Tracing (CT) in households of cases;Isolation Centres (IC), for cases not requiring hospitalisation;community health worker-led Mass Symptom Screening and diagnostic testing for symptomatic individuals (MS);and Quarantine Centres (QC), for contacts who test negative. Given uncertainties about epidemic dynamics in South Africa, we evaluated two main epidemic scenarios over 360 days, with effective reproduction numbers (R e ) of 1.5 and 1.2. We compared HT, HT+CT, HT+CT+IC, HT+CT+IC+MS, HT+CT+IC+QC, and HT+CT+IC+MS+QC, considering strategies with incremental cost-effectiveness ratio (ICER) <US$1,290/year-of-life saved (YLS) to be cost-effective. Findings With R e 1.5, HT resulted in the most COVID-19 deaths and lowest costs over 360 days. Compared with HT, HT+CT+IC+MS reduced mortality by 76%, increased costs by 16%, and was cost-effective (ICER $350/YLS). HT+CT+IC+MS+QC provided the greatest reduction in mortality, but increased costs by 95% compared with HT+CT+IC+MS and was not cost-effective (ICER $8,000/YLS). With R e 1.2, HT+CT+IC+MS was the least costly strategy, and HT+CT+IC+MS+QC was not cost-effective (ICER $294,320/YLS). Interpretation In South Africa, a strategy of household contact tracing, isolation, and mass symptom screening would substantially reduce COVID-19 mortality and be cost-effective. Adding quarantine centres for COVID-19 contacts is not cost-effective.

Clinical Impact, Costs, and Cost-effectiveness of Expanded Severe Acute Respiratory Syndrome Coronavirus 2 Testing in Massachusetts.

BACKGROUND: We projected the clinical and economic impact of alternative testing strategies on coronavirus disease 2019 (COVID-19) incidence and mortality in Massachusetts using a microsimulation model. METHODS: We compared 4 testing strategies: (1) hospitalized: polymerase chain reaction (PCR) testing only for patients with severe/critical symptoms warranting hospitalization; (2) symptomatic: PCR for any COVID-19-consistent symptoms, with self-isolation if positive; (3) symptomatic + asymptomatic once: symptomatic and 1-time PCR for the entire population; and (4) symptomatic + asymptomatic monthly: symptomatic with monthly retesting for the entire population. We examined effective reproduction numbers (Re = 0.9-2.0) at which policy conclusions would change. We assumed homogeneous mixing among the Massachusetts population (excluding those residing in long-term care facilities). We used published data on disease progression and mortality, transmission, PCR sensitivity/specificity (70%/100%), and costs. Model-projected outcomes included infections, deaths, tests performed, hospital-days, and costs over 180 days, as well as incremental cost-effectiveness ratios (ICERs, $/quality-adjusted life-year [QALY]). RESULTS: At Re = 0.9, symptomatic + asymptomatic monthly vs hospitalized resulted in a 64% reduction in infections and a 46% reduction in deaths, but required >66-fold more tests/day with 5-fold higher costs. Symptomatic + asymptomatic monthly had an ICER <$100 000/QALY only when Re ≥1.6; when test cost was ≤$3, every 14-day testing was cost-effective at all Re examined. CONCLUSIONS: Testing people with any COVID-19-consistent symptoms would be cost-saving compared to testing only those whose symptoms warrant hospital care. Expanding PCR testing to asymptomatic people would decrease infections, deaths, and hospitalizations. Despite modest sensitivity, low-cost, repeat screening of the entire population could be cost-effective in all epidemic settings.

College Campuses and COVID-19 Mitigation: Clinical and Economic Value.

BACKGROUND: Colleges in the United States are determining how to operate safely amid the coronavirus disease 2019 (COVID-19) pandemic. OBJECTIVE: To examine the clinical outcomes, cost, and cost-effectiveness of COVID-19 mitigation strategies on college campuses. DESIGN: The Clinical and Economic Analysis of COVID-19 interventions (CEACOV) model, a dynamic microsimulation model, was used to examine alternative mitigation strategies. The CEACOV model tracks infections accrued by students and faculty, accounting for community transmissions. DATA SOURCES: Data from published literature were used to obtain parameters related to COVID-19 and contact-hours. TARGET POPULATION: Undergraduate students and faculty at U.S. colleges. TIME HORIZON: One semester (105 days). PERSPECTIVE: Modified societal. INTERVENTION: COVID-19 mitigation strategies, including social distancing, masks, and routine laboratory screening. OUTCOME MEASURES: Infections among students and faculty per 5000 students and per 1000 faculty, isolation days, tests, costs, cost per infection prevented, and cost per quality-adjusted life-year (QALY). RESULTS OF BASE-CASE ANALYSIS: Among students, mitigation strategies reduced COVID-19 cases from 3746 with no mitigation to 493 with extensive social distancing and masks, and further to 151 when laboratory testing was added among asymptomatic persons every 3 days. Among faculty, these values were 164, 28, and 25 cases, respectively. Costs ranged from about $0.4 million for minimal social distancing to about $0.9 million to $2.1 million for strategies involving laboratory testing ($10 per test), depending on testing frequency. Extensive social distancing with masks cost $170 per infection prevented ($49 200 per QALY) compared with masks alone. Adding routine laboratory testing increased cost per infection prevented to between $2010 and $17 210 (cost per QALY gained, $811 400 to $2 804 600). RESULTS OF SENSITIVITY ANALYSIS: Results were most sensitive to test costs. LIMITATION: Data are from multiple sources. CONCLUSION: Extensive social distancing with a mandatory mask-wearing policy can prevent most COVID-19 cases on college campuses and is very cost-effective. Routine laboratory testing would prevent 96% of infections and require low-cost tests to be economically attractive. PRIMARY FUNDING SOURCE: National Institutes of Health.

Outcomes from an infectious disease physician-guided evaluation of hospitalized persons under investigation for coronavirus disease 2019 (COVID-19) at a large US academic medical center.

We describe an approach to the evaluation and isolation of hospitalized persons under investigation (PUIs) for coronavirus disease 2019 (COVID-19) at a large US academic medical center. Only a small proportion (2.9%) of PUIs with 1 or more repeated severe acute respiratory coronavirus virus 2 (SARS-CoV-2) nucleic acid amplification tests (NAATs) after a negative NAAT were diagnosed with COVID-19.

Clinical, Laboratory, and Radiologic Characteristics of Patients With Initial False-Negative Severe Acute Respiratory Syndrome Coronavirus 2 Nucleic Acid Amplification Test Results.

BACKGROUND: Concerns about false-negative (FN) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid amplification tests (NAATs) have prompted recommendations for repeat testing if suspicion for coronavirus disease 2019 (COVID-19) infection is moderate to high. However, the frequency of FNs and patient characteristics associated with FNs are poorly understood. METHODS: We retrospectively reviewed test results from 15 011 adults who underwent ≥1 SARS-CoV-2 NAATs; 2699 had an initial negative NAAT and repeat testing. We defined FNs as ≥1 negative NAATs followed by a positive NAAT within 14 days during the same episode of illness. We stratified subjects with FNs by duration of symptoms before the initial FN test (≤5 days versus >5 days) and examined their clinical, radiologic, and laboratory characteristics. RESULTS: Sixty of 2699 subjects (2.2%) had a FN result during the study period. The weekly frequency of FNs among subjects with repeat testing peaked at 4.4%, coinciding with peak NAAT positivity (38%). Most subjects with FNs had symptoms (52 of 60; 87%) and chest radiography (19 of 32; 59%) consistent with COVID-19. Of the FN NAATs, 18 of 60 (30%) were performed early (ie, ≤1 day of symptom onset), and 18 of 60 (30%) were performed late (ie, >7 days after symptom onset) in disease. Among 17 subjects with 2 consecutive FNs on NP NAATs, 9 (53%) provided lower respiratory tract (LRT) specimens for testing, all of which were positive. CONCLUSIONS: Our findings support repeated NAATs among symptomatic patients, particularly during periods of higher COVID-19 incidence. The LRT testing should be prioritized to increase yield among patients with high clinical suspicion for COVID-19.

Patient characteristics associated with SARS-CoV-2 infection in parturients admitted for labour and delivery in Massachusetts during the spring 2020 surge: A prospective cohort study.

BACKGROUND: While studies from large cities affected by coronavirus disease 2019 (COVID-19) have reported on the prevalence of SARS-CoV-2 in the context of universal testing during admission for delivery, the patient demographic, social and clinical factors associated with SARS-CoV-2 infection in pregnant women are not fully understood. OBJECTIVE: To evaluate the epidemiological factors associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in women admitted for labour and delivery, in the context of universal screening at four Boston-area hospitals. METHODS: In this prospective cohort study, we reviewed the health records of all women admitted for labour and delivery at four hospitals from the largest health system in Massachusetts between 19 April 2020 and 27 June 2020. We calculated the risk of SARS-CoV-2 infection, including asymptomatic infection. We calculated associations between SARS-CoV-2 infection and demographic and clinical characteristics. RESULTS: A total of 93 patients (3.2%, 95% confidence interval 2.5, 3.8) tested positive for SARS-CoV-2 infection on admission for labour and delivery out of 2945 patients included in the analysis; 80 (86.0%) of the patients who tested positive were asymptomatic at the time of testing. Factors associated with SARS-CoV-2 infection included the following: younger age, obesity, African American or Hispanic race/ethnicity, residence in heavily affected communities (as measured in cases reported per capita), presence of a household member with known SARS-CoV-2 infection, non-health care essential worker occupation and MassHealth or Medicaid insurance compared to commercial insurance. 93.8% of patients testing positive for SARS-CoV-2 on admission had one or more identifiable factors associated with disease acquisition. CONCLUSIONS: In this large sample of deliveries during the height of the surge in infections during the spring of 2020, SARS-CoV-2 infection was largely concentrated in patients with distinct demographic characteristics, those largely from disadvantaged communities. Racial disparities seen in pregnancy persist with respect to SARS-CoV-2 infection.

Cost-effectiveness of public health strategies for COVID-19 epidemic control in South Africa: a microsimulation modelling study.

BACKGROUND: Health-care resource constraints in low-income and middle-income countries necessitate the identification of cost-effective public health interventions to address COVID-19. We aimed to develop a dynamic COVID-19 microsimulation model to assess clinical and economic outcomes and cost-effectiveness of epidemic control strategies in KwaZulu-Natal province, South Africa. METHODS: We compared different combinations of five public health interventions: health-care testing alone, where diagnostic testing is done only for individuals presenting to health-care centres; contact tracing in households of cases; isolation centres, for cases not requiring hospital admission; mass symptom screening and molecular testing for symptomatic individuals by community health-care workers; and quarantine centres, for household contacts who test negative. We calibrated infection transmission rates to match effective reproduction number (Re) estimates reported in South Africa. We assessed two main epidemic scenarios for a period of 360 days, with an Re of 1·5 and 1·2. Strategies with incremental cost-effectiveness ratio (ICER) of less than US$3250 per year of life saved were considered cost-effective. We also did sensitivity analyses by varying key parameters (Re values, molecular testing sensitivity, and efficacies and costs of interventions) to determine the effect on clinical and cost projections. FINDINGS: When Re was 1·5, health-care testing alone resulted in the highest number of COVID-19 deaths during the 360-day period. Compared with health-care testing alone, a combination of health-care testing, contact tracing, use of isolation centres, mass symptom screening, and use of quarantine centres reduced mortality by 94%, increased health-care costs by 33%, and was cost-effective (ICER $340 per year of life saved). In settings where quarantine centres were not feasible, a combination of health-care testing, contact tracing, use of isolation centres, and mass symptom screening was cost-effective compared with health-care testing alone (ICER $590 per year of life saved). When Re was 1·2, health-care testing, contact tracing, use of isolation centres, and use of quarantine centres was the least costly strategy, and no other strategies were cost-effective. In sensitivity analyses, a combination of health-care testing, contact tracing, use of isolation centres, mass symptom screening, and use of quarantine centres was generally cost-effective, with the exception of scenarios in which Re was 2·6 and when efficacies of isolation centres and quarantine centres for transmission reduction were reduced. INTERPRETATION: In South Africa, strategies involving household contact tracing, isolation, mass symptom screening, and quarantining household contacts who test negative would substantially reduce COVID-19 mortality and would be cost-effective. The optimal combination of interventions depends on epidemic growth characteristics and practical implementation considerations. FUNDING: US National Institutes of Health, Royal Society, Wellcome Trust.

Cost-effectiveness of public health strategies for COVID-19 epidemic control in South Africa: a microsimulation modelling study.

BACKGROUND: Healthcare resource constraints in low and middle-income countries necessitate selection of cost-effective public health interventions to address COVID-19. METHODS: We developed a dynamic COVID-19 microsimulation model to evaluate clinical and economic outcomes and cost-effectiveness of epidemic control strategies in KwaZulu-Natal, South Africa. Interventions assessed were Healthcare Testing (HT), where diagnostic testing is performed only for those presenting to healthcare centres; Contact Tracing (CT) in households of cases; Isolation Centres (IC), for cases not requiring hospitalisation; community health worker-led Mass Symptom Screening and molecular testing for symptomatic individuals (MS); and Quarantine Centres (QC), for household contacts who test negative. Given uncertainties about epidemic dynamics in South Africa, we evaluated two main epidemic scenarios over 360 days, with effective reproduction numbers (Re) of 1·5 and 1·2. We compared HT, HT+CT, HT+CT+IC, HT+CT+IC+MS, HT+CT+IC+QC, and HT+CT+IC+MS+QC, considering strategies with incremental cost-effectiveness ratio (ICER)