scholarly journals Effectiveness of non-pharmaceutical public health interventions against COVID-19: A systematic review and meta-analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260371
Author(s):  
Shabnam Iezadi ◽  
Kamal Gholipour ◽  
Saber Azami-Aghdash ◽  
Akbar Ghiasi ◽  
Aziz Rezapour ◽  
...  

Non-Pharmaceutical Public Health Interventions (NPHIs) have been used by different countries to control the spread of the COVID-19. Despite available evidence regarding the effectiveness of NPHSs, there is still no consensus about how policymakers can trust these results. Studies on the effectiveness of NPHSs are single studies conducted in specific communities. Therefore, they cannot individually prove if these interventions have been effective in reducing the spread of the infection and its adverse health outcomes. In this systematic review, we aimed to examine the effects of NPHIs on the COVID-19 case growth rate, death growth rate, Intensive Care Unit (ICU) admission, and reproduction number in countries, where NPHIs have been implemented. We searched relevant electronic databases, including Medline (via PubMed), Scopus, CINAHL, Web of Science, etc. from late December 2019 to February 1, 2021. The key terms were primarily drawn from Medical Subject Heading (MeSh and Emtree), literature review, and opinions of experts. Peer-reviewed quasi-experimental studies were included in the review. The PROSPERO registration number is CRD42020186855. Interventions were NPHIs categorized as lockdown, stay-at-home orders, social distancing, and other interventions (mask-wearing, contact tracing, and school closure). We used PRISMA 2020 guidance for abstracting the data and used Cochrane Effective Practice and Organization of Practice (EPOC) Risk of Bias Tool for quality appraisal of the studies. Hartung-Knapp-Sidik-Jonkman random-effects model was performed. Main outcomes included COVID-19 case growth rate (percentage daily changes), COVID-19 mortality growth rate (percentage daily changes), COVID-19 ICU admission (percentage daily changes), and COVID-19 reproduction number changes. Our search strategies in major databases yielded 12,523 results, which decreased to 7,540 articles after eliminating duplicates. Finally, 35 articles qualified to be included in the systematic review among which 23 studies were included in the meta-analysis. Although studies were from both low-income and high-income countries, the majority of them were from the United States (13 studies) and China (five studies). Results of the meta-analysis showed that adoption of NPHIs has resulted in a 4.68% (95% CI, -6.94 to -2.78) decrease in daily case growth rates, 4.8% (95 CI, -8.34 to -1.40) decrease in daily death growth rates, 1.90 (95% CI, -2.23 to -1.58) decrease in the COVID-19 reproduction number, and 16.5% (95% CI, -19.68 to -13.32) decrease in COVID-19 daily ICU admission. A few studies showed that, early enforcement of lockdown, when the incidence rate is not high, contributed to a shorter duration of lockdown and a lower increase of the case growth rate in the post-lockdown era. The majority of NPHIs had positive effects on restraining the COVID-19 spread. With the problems that remain regarding universal access to vaccines and their effectiveness and considering the drastic impact of the nationwide lockdown and other harsh restrictions on the economy and people’s life, such interventions should be mitigated by adopting other NPHIs such as mass mask-wearing, patient/suspected case isolation strategies, and contact tracing. Studies need to address the impact of NPHIs on the population’s other health problems than COVID-19.

2021 ◽  
Vol 47 (7/8) ◽  
pp. 329-338
Author(s):  
Jianhong Wu ◽  
Francesca Scarabel ◽  
Zachary McCarthy ◽  
Yanyu Xiao ◽  
Nicholas H Ogden

Background: When public health interventions are being loosened after several days of decline in the number of coronavirus disease 2019 (COVID-19) cases, it is of critical importance to identify potential strategies to ease restrictions while mitigating a new wave of more transmissible variants of concern (VOCs). We estimated the necessary enhancements to public health interventions for a partial reopening of the economy while avoiding the worst consequences of a new outbreak, associated with more transmissible VOCs. Methods: We used a transmission dynamics model to quantify conditions that combined public health interventions must meet to reopen the economy without a large outbreak. These conditions are those that maintain the control reproduction number below unity, while accounting for an increase in transmissibility due to VOC. Results: We identified combinations of the proportion of individuals exposed to the virus who are traced and quarantined before becoming infectious, the proportion of symptomatic individuals confirmed and isolated, and individual daily contact rates needed to ensure the control reproduction number remains below unity. Conclusion: Our analysis indicates that the success of restrictive measures including lockdown and stay-at-home orders, as reflected by a reduction in number of cases, provides a narrow window of opportunity to intensify case detection and contact tracing efforts to prevent a new wave associated with circulation of more transmissible VOCs.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Imen Ayouni ◽  
Jihen Maatoug ◽  
Wafa Dhouib ◽  
Nawel Zammit ◽  
Sihem Ben Fredj ◽  
...  

Abstract Background In December 2019, a novel coronavirus (2019-nCoV) was recognized in Wuhan, China. It was characterised by rapid spread causing a pandemic. Multiple public health interventions have been implemented worldwide to decrease the transmission of the 2019 novel coronavirus disease (COVID-19). The objective of this systematic review is to evaluate the implemented public health interventions to control the spread of the outbreak of COVID-19. Methods: We systematically searched PubMed, Science Direct and MedRxiv for relevant articles published in English up to March 16, 2021. We included quasi experimental studies, clinical trials, cohort studies, longitudinal studies, case-control studies and interrupted time series. We included the studies that investigated the effect of the implemented public health measures to prevent and control the outbreak of 2019 novel coronavirus disease (COVID-19). Results The database search using the predefined combinations of Mesh terms found 13,497 studies of which 3595 in PubMed, 7393 in Science Direct 2509 preprints in MedRxiv. After removal of the duplicates and the critical reading only 18 articles were included in this systematic review and processed for data extraction. Conclusions Public health interventions and non-pharmaceutical measurements were effective in decreasing the transmission of COVID-19. The included studies showed that travel restrictions, borders measures, quarantine of travellers arriving from affected countries, city lockdown, restrictions of mass gathering, isolation and quarantine of confirmed cases and close contacts, social distancing measures, compulsory mask wearing, contact tracing and testing, school closures and personal protective equipment use among health workers were effective in mitigating the spread of COVID-19.


Author(s):  
Anil Babu Payedimarri ◽  
Diego Concina ◽  
Luigi Portinale ◽  
Massimo Canonico ◽  
Deborah Seys ◽  
...  

Artificial Intelligence (AI) and Machine Learning (ML) have expanded their utilization in different fields of medicine. During the SARS-CoV-2 outbreak, AI and ML were also applied for the evaluation and/or implementation of public health interventions aimed to flatten the epidemiological curve. This systematic review aims to evaluate the effectiveness of the use of AI and ML when applied to public health interventions to contain the spread of SARS-CoV-2. Our findings showed that quarantine should be the best strategy for containing COVID-19. Nationwide lockdown also showed positive impact, whereas social distancing should be considered to be effective only in combination with other interventions including the closure of schools and commercial activities and the limitation of public transportation. Our findings also showed that all the interventions should be initiated early in the pandemic and continued for a sustained period. Despite the study limitation, we concluded that AI and ML could be of help for policy makers to define the strategies for containing the COVID-19 pandemic.


2016 ◽  
Vol 70 (Suppl 1) ◽  
pp. A96.2-A96
Author(s):  
R Mason ◽  
E Anwar ◽  
B Collins ◽  
R Cookson ◽  
S Capewell ◽  
...  

2017 ◽  
Vol 17 (1) ◽  
Author(s):  
Ginny Brunton ◽  
James Thomas ◽  
Alison O’Mara-Eves ◽  
Farah Jamal ◽  
Sandy Oliver ◽  
...  

2020 ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego

Abstract To date, many studies have argued the potential impact of public health interventions on flattening the epidemic curve of SARS-CoV-2. Most of them have focused on simulating the impact of interventions in a region of interest by manipulating contact patterns and key transmission parameters to reflect different scenarios. Our study looks into the evolution of the daily effective reproduction number during the epidemic via a stochastic transmission model. We found this measure (although model-dependent) provides an early signal of the efficacy of containment measures. This epidemiological parameter when updated in real-time can also provide better predictions of future outbreaks. Our results found a substantial variation in the effect of public health interventions on the dynamic of SARS-CoV-2 transmission over time and across countries, that could not be explained solely by the timing and number of the adopted interventions. This suggests that further knowledge about the idiosyncrasy of their implementation and effectiveness is required. Although sustained containment measures have successfully lowered growth in disease transmission, more than half of the 101 studied countries failed to maintain the effective reproduction number close to or below 1. This resulted in continued growth in reported cases. Finally, we were able to predict with reasonable accuracy which countries would experience outbreaks in the next 30 days.


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