1
|
Duval D, Evans B, Sanders A, Hill J, Simbo A, Kavoi T, Lyell I, Simmons Z, Qureshi M, Pearce-Smith N, Arevalo CR, Beck CR, Bindra R, Oliver I. Non-pharmaceutical interventions to reduce COVID-19 transmission in the UK: a rapid mapping review and interactive evidence gap map. J Public Health (Oxf) 2024; 46:e279-e293. [PMID: 38426578 PMCID: PMC11141784 DOI: 10.1093/pubmed/fdae025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 01/15/2024] [Accepted: 01/23/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Non-pharmaceutical interventions (NPIs) were crucial in the response to the COVID-19 pandemic, although uncertainties about their effectiveness remain. This work aimed to better understand the evidence generated during the pandemic on the effectiveness of NPIs implemented in the UK. METHODS We conducted a rapid mapping review (search date: 1 March 2023) to identify primary studies reporting on the effectiveness of NPIs to reduce COVID-19 transmission. Included studies were displayed in an interactive evidence gap map. RESULTS After removal of duplicates, 11 752 records were screened. Of these, 151 were included, including 100 modelling studies but only 2 randomized controlled trials and 10 longitudinal observational studies.Most studies reported on NPIs to identify and isolate those who are or may become infectious, and on NPIs to reduce the number of contacts. There was an evidence gap for hand and respiratory hygiene, ventilation and cleaning. CONCLUSIONS Our findings show that despite the large number of studies published, there is still a lack of robust evaluations of the NPIs implemented in the UK. There is a need to build evaluation into the design and implementation of public health interventions and policies from the start of any future pandemic or other public health emergency.
Collapse
Affiliation(s)
- D Duval
- Research, Evidence and Knowledge Division, UK Health Security Agency (UKHSA), London E14 5EA, UK
| | - B Evans
- Research, Evidence and Knowledge Division, UK Health Security Agency (UKHSA), London E14 5EA, UK
| | - A Sanders
- Research, Evidence and Knowledge Division, UK Health Security Agency (UKHSA), London E14 5EA, UK
| | - J Hill
- Clinical and Public Health Response Division, UKHSA, London E14 5EA, UK
| | - A Simbo
- Evaluation and Epidemiological Science Division, UKHSA, Colindale NW9 5EQ, UK
| | - T Kavoi
- Cheshire and Merseyside Health Protection Team, UKHSA, Liverpool L3 1DS, UK
| | - I Lyell
- Greater Manchester Health Protection Team, UKHSA, Manchester M1 3BN, UK
| | - Z Simmons
- Research, Evidence and Knowledge Division, UK Health Security Agency (UKHSA), London E14 5EA, UK
| | - M Qureshi
- Clinical and Public Health Response Division, UKHSA, London E14 5EA, UK
| | - N Pearce-Smith
- Research, Evidence and Knowledge Division, UK Health Security Agency (UKHSA), London E14 5EA, UK
| | - C R Arevalo
- Research, Evidence and Knowledge Division, UK Health Security Agency (UKHSA), London E14 5EA, UK
| | - C R Beck
- Evaluation and Epidemiological Science Division, UKHSA, Salisbury SP4 0JG, UK
| | - R Bindra
- Clinical and Public Health Response Division, UKHSA, London E14 5EA, UK
| | - I Oliver
- Director General Science and Research and Chief Scientific Officer, UKHSA, London E14 5EA, UK
| |
Collapse
|
2
|
Liu Y, Yin Y, Ward MP, Li K, Chen Y, Duan M, Wong PPY, Hong J, Huang J, Shi J, Zhou X, Chen X, Xu J, Yuan R, Kong L, Zhang Z. Optimization of Screening Strategies for COVID-19: Scoping Review. JMIR Public Health Surveill 2024; 10:e44349. [PMID: 38412011 PMCID: PMC10933748 DOI: 10.2196/44349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 06/29/2023] [Accepted: 11/21/2023] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND COVID-19 screening is an effective nonpharmaceutical intervention for identifying infected individuals and interrupting viral transmission. However, questions have been raised regarding its effectiveness in controlling the spread of novel variants and its high socioeconomic costs. Therefore, the optimization of COVID-19 screening strategies has attracted great attention. OBJECTIVE This review aims to summarize the evidence and provide a reference basis for the optimization of screening strategies for the prevention and control of COVID-19. METHODS We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. We conducted a scoping review of the present publications on the optimization of COVID-19 screening strategies. We searched the PubMed, Web of Science, and Elsevier ScienceDirect databases for publications up to December 31, 2022. English publications related to screening and testing strategies for COVID-19 were included. A data-charting form, jointly developed by 2 reviewers, was used for data extraction according to the optimization directions of the screening strategies. RESULTS A total of 2770 unique publications were retrieved from the database search, and 95 abstracts were retained for full-text review. There were 62 studies included in the final review. We summarized the results in 4 major aspects: the screening population (people at various risk conditions such as different regions and occupations; 12/62, 19%), the timing of screening (when the target population is tested before travel or during an outbreak; 12/62, 19%), the frequency of screening (appropriate frequencies for outbreak prevention, outbreak response, or community transmission control; 6/62, 10%), and the screening and detection procedure (the choice of individual or pooled detection and optimization of the pooling approach; 35/62, 56%). CONCLUSIONS This review reveals gaps in the optimization of COVID-19 screening strategies and suggests that a number of factors such as prevalence, screening accuracy, effective allocation of resources, and feasibility of strategies should be carefully considered in the development of future screening strategies.
Collapse
Affiliation(s)
- Yuanhua Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yun Yin
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Michael P Ward
- Sydney School of Veterinary Science, The University of Sydney, NSW, Australia
| | - Ke Li
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yue Chen
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Mengwei Duan
- Department of Mathematics and Physics, North China Electric Power University, Baoding, China
| | | | - Jie Hong
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jiaqi Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jin Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Xuan Zhou
- Department of Mathematics and Physics, North China Electric Power University, Baoding, China
| | - Xi Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jiayao Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Rui Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Lingcai Kong
- Department of Mathematics and Physics, North China Electric Power University, Baoding, China
| | - Zhijie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| |
Collapse
|