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

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Abstract

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 (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$3,250/year-of-life saved (YLS) cost-effective. In sensitivity analyses, we varied R _e, molecular testing sensitivity, and efficacies and costs of interventions.

Findings

With R _e 1·5, HT resulted in the most COVID-19 deaths over 360 days. Compared with HT, HT+ CT+ IC+ MS+ QC reduced mortality by 94%, increased costs by 33%, and was cost-effective (ICER $340/YLS). In settings where quarantine centres cannot be implemented, HT+ CT+ IC+ MS was cost-effective compared with HT (ICER $590/YLS). With R _e 1·2, HT+ CT+ IC+ QC was the least costly strategy, and no other strategy was cost-effective. HT+ CT+ IC+ MS+ QC was cost-effective in many sensitivity analyses; notable exceptions were when R _e was 2·6 and when efficacies of ICs and QCs 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 be cost-effective. The optimal combination of interventions depends on epidemic growth characteristics and practical implementation considerations.

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Most cited references 25

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Detection of SARS-CoV-2 in Different Types of Clinical Specimens

Wenling Wang, Yanli Xu, Ruqin Gao … (2020)

This study describes results of PCR and viral RNA testing for SARS-CoV-2 in bronchoalveolar fluid, sputum, feces, blood, and urine specimens from patients with COVID-19 infection in China to identify possible means of non-respiratory transmission.

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Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study

Annemarie Docherty, Ewen Harrison, Christopher A Green … (2020)

Abstract Objective To characterise the clinical features of patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United Kingdom during the growth phase of the first wave of this outbreak who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study, and to explore risk factors associated with mortality in hospital. Design Prospective observational cohort study with rapid data gathering and near real time analysis. Setting 208 acute care hospitals in England, Wales, and Scotland between 6 February and 19 April 2020. A case report form developed by ISARIC and WHO was used to collect clinical data. A minimal follow-up time of two weeks (to 3 May 2020) allowed most patients to complete their hospital admission. Participants 20 133 hospital inpatients with covid-19. Main outcome measures Admission to critical care (high dependency unit or intensive care unit) and mortality in hospital. Results The median age of patients admitted to hospital with covid-19, or with a diagnosis of covid-19 made in hospital, was 73 years (interquartile range 58-82, range 0-104). More men were admitted than women (men 60%, n=12 068; women 40%, n=8065). The median duration of symptoms before admission was 4 days (interquartile range 1-8). The commonest comorbidities were chronic cardiac disease (31%, 5469/17 702), uncomplicated diabetes (21%, 3650/17 599), non-asthmatic chronic pulmonary disease (18%, 3128/17 634), and chronic kidney disease (16%, 2830/17 506); 23% (4161/18 525) had no reported major comorbidity. Overall, 41% (8199/20 133) of patients were discharged alive, 26% (5165/20 133) died, and 34% (6769/20 133) continued to receive care at the reporting date. 17% (3001/18 183) required admission to high dependency or intensive care units; of these, 28% (826/3001) were discharged alive, 32% (958/3001) died, and 41% (1217/3001) continued to receive care at the reporting date. Of those receiving mechanical ventilation, 17% (276/1658) were discharged alive, 37% (618/1658) died, and 46% (764/1658) remained in hospital. Increasing age, male sex, and comorbidities including chronic cardiac disease, non-asthmatic chronic pulmonary disease, chronic kidney disease, liver disease and obesity were associated with higher mortality in hospital. Conclusions ISARIC WHO CCP-UK is a large prospective cohort study of patients in hospital with covid-19. The study continues to enrol at the time of this report. In study participants, mortality was high, independent risk factors were increasing age, male sex, and chronic comorbidity, including obesity. This study has shown the importance of pandemic preparedness and the need to maintain readiness to launch research studies in response to outbreaks. Study registration ISRCTN66726260.

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Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

Joel Hellewell, Sam Abbott, Amy Gimma … (2020)

Summary Background Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19. Methods We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R 0), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings Simulated outbreaks starting with five initial cases, an R 0 of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R 0 was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R 0 of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R 0 of 2·5 more than 70% of contacts had to be traced, and for an R 0 of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R 0 was 1·5. For R 0 values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. Funding Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK.

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Author and article information

Journal

Journal ID (nlm-ta): medRxiv

Journal ID (publisher-id): MEDRXIV

Title: medRxiv

Publisher: Cold Spring Harbor Laboratory

Publication date (Electronic): 11 October 2020

Electronic Location Identifier: 2020.06.29.20140111

Affiliations

[1 ]Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA

[2 ]Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA

[3 ]Harvard Medical School, Boston, MA, USA

[4 ]Department of Epidemiology and Harvard Center for Population & Development Studies, Harvard T.H. Chan School of Public Health, Boston, MA, USA

[5 ]Africa Health Research Institute, KwaZulu-Natal, South Africa

[6 ]Institute for Global Health, University College London, London, UK

[7 ]MRC/Wits Rural Public Health & Health Transitions Research Unit (Agincourt), University of Witwatersrand, South Africa

[8 ]Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA

[9 ]Harvard University Center for AIDS Research, Cambridge, MA, USA

[10 ]Division of General Academic Pediatrics, Massachusetts General Hospital, Boston, MA, USA

[11 ]Desmond Tutu HIV Foundation, University of Cape Town, Cape Town, South Africa

[12 ]KwaZulu-Natal Research Innovation and Sequencing (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa

[13 ]Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA

[14 ]Orthopedic and Arthritis Center for Outcomes Research (OrACORe), Department of Orthopedic Surgery, Brigham and Women’s Hospital, Boston, MA, USA

[15 ]Policy and Innovation eValuation in Orthopedic Treatments (PIVOT) Center, Department of Orthopedic Surgery, Brigham and Women’s Hospital, Boston, MA, USA

[16 ]Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA

[17 ]Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA

Author notes

[*]

PK and MJS contributed equally to this work.

AUTHOR ROLES

All authors contributed substantively to this manuscript in the following ways: study and model design (all authors), data analysis (KPR, FMS, JHAF, GH, KPF, KAF, PK, MJS), interpretation of results (all authors), drafting the manuscript (KPR, MJS), critical revision of the manuscript (all authors) and final approval of submitted version (all authors).

Corresponding Author: Krishna P. Reddy, MD, MS, Medical Practice Evaluation Center, Massachusetts General Hospital, 100 Cambridge Street, Suite 1600, Boston, MA 02114, USA, Phone: +1 617-726-1993, Fax: +1 617-726-4120, kpreddy@ 123456mgh.harvard.edu

Article

DOI: 10.1101/2020.06.29.20140111

PMC ID: 7340205

PubMed ID: 32637979

SO-VID: f7cad229-8e00-4987-9062-02302a8aa56a

License:

It is made available under a CC-BY-NC-ND 4.0 International license.

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

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Abstract

Background

Methods

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Interpretation

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UCL: Covid-19 Research

Most cited references 25

Detection of SARS-CoV-2 in Different Types of Clinical Specimens

Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study

Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

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