key: cord-0921785-fmqidh3n
authors: Rizvi, Rubina F; Craig, Kelly J Thomas; Hekmat, Rezzan; Reyes, Fredy; South, Brett; Rosario, Bedda; Kassler, William J; Jackson, Gretchen P
title: Effectiveness of non-pharmaceutical interventions related to social distancing on respiratory viral infectious disease outcomes: A rapid evidence-based review and meta-analysis
date: 2021-06-06
journal: SAGE Open Med
DOI: 10.1177/20503121211022973
sha: 76d128088a3873a705923fad765834c534500a6e
doc_id: 921785
cord_uid: fmqidh3n

OBJECTIVES: Non-pharmaceutical interventions (e.g. quarantine and isolation) are used to mitigate and control viral infectious disease, but their effectiveness has not been well studied. For COVID-19, disease control efforts will rely on non-pharmaceutical interventions until pharmaceutical interventions become widely available, while non-pharmaceutical interventions will be of continued importance thereafter. METHODS: This rapid evidence-based review provides both qualitative and quantitative analyses of the effectiveness of social distancing non-pharmaceutical interventions on disease outcomes. Literature was retrieved from MEDLINE, Google Scholar, and pre-print databases (BioRxiv.org, MedRxiv.org, and Wellcome Open Research). RESULTS: Twenty-eight studies met inclusion criteria (n = 28). Early, sustained, and combined application of various non-pharmaceutical interventions could mitigate and control primary outbreaks and prevent more severe secondary or tertiary outbreaks. The strategic use of non-pharmaceutical interventions decreased incidence, transmission, and/or mortality across all interventions examined. The pooled attack rates for no non-pharmaceutical intervention, single non-pharmaceutical interventions, and multiple non-pharmaceutical interventions were 42% (95% confidence interval = 30% – 55%), 29% (95% confidence interval = 23% – 36%), and 22% (95% confidence interval = 16% – 29%), respectively. CONCLUSION: Implementation of multiple non-pharmaceutical interventions at key decision points for public health could effectively facilitate disease mitigation and suppression until pharmaceutical interventions become available. Dynamics around R(0) values, the susceptibility of certain high-risk patient groups to infection, and the probability of asymptomatic cases spreading disease should be considered.

In the absence of a vaccine, mitigation of the coronavirus disease 2019 (COVID-19) pandemic requires non-pharmaceutical interventions (NPIs), such as social distancing, increased hand hygiene, mask wearing, and surface decontamination, which have been implemented across the globe. 1 However, the effectiveness of NPIs is difficult to measure, especially for a rapidly evolving disease like COVID- 19 . To help understand the implications of using NPIs, singly Effectiveness of non-pharmaceutical interventions related to social distancing on respiratory viral infectious disease outcomes: A rapid evidence-based review and meta-analysis or in combination with other NPIs or pharmaceutical interventions (PIs), epidemiologists are relying on evidence from retrospective studies of past outbreaks to manage the current COVID-19 pandemic. With emerging but limited current evidence around COVID-19, the effectiveness of NPIs to mitigate and control other viral diseases from retrospective studies may offer valuable information to improve pandemic preparedness and response.

Social distancing NPIs have historically decreased the spread of viral infectious diseases. These interventions lower the likelihood that a healthy individual will come in contact with an infected person, help limit disease spread, and promote suppression of new cases, such as in the 1918 influenza A pandemic, 2,3 epidemics related to coronavirus (e.g. 2003 severe acute respiratory syndrome coronavirus (SARS-CoV)), 4 and various others. Studies have been recently conducted to show the observed impact of NPIs on a variety of pathogens, including influenza and norovirus, during the COVID-19 pandemic. 5, 6 The objective of this study is to identify and synthesize evidence regarding the effectiveness of social distancing NPIs on respiratory infectious viral disease outcomes. This rapid evidence-based review and meta-analysis focuses on studies describing the implementation and assessment of social distancing-related NPIs, including general distancing strategies, quarantine, and/or isolation using single or multiple interventions during respiratory viral epidemics or pandemics. The knowledge gained from this review could help public health policy makers, clinicians, researchers, and so on to strategically plan and implement these interventions in order to limit the spread and mitigation of COVID-19 or other future respiratory viral pandemics.

A rapid evidence-based review 7, 8 was conducted to identify studies examining the effectiveness of single or multiple social distancing NPIs on infectious viral disease (pandemic or epidemic) outcomes (e.g. incidence, transmission, and mortality) with comparisons to examine the effects of the intervention, its timing, and/or combination(s) of interventions. Included studies with the following social distancing NPIs were clustered into three main groups: (1) General: voluntary or mandatory steps taken to reduce face-to-face interactions among people in the community; (2) Quarantine: imposed separation or restriction of movement of persons who are exposed, who may or may not be infected but are not ill, and may become infectious to others; and (3) Isolation: the separation and confinement of individuals known or suspected to be infectious or ill with a contagious disease in order to prevent them from transmitting the disease to others. Primary or secondary studies published in English, conducted in humans, and with an abstract, were considered. Supplementary Tables I and II present the study methodology details.

A search of published literature in MEDLINE via PubMed, Google Scholar, and pre-print databases (BioRxiv.org, MedRxiv.org, and Wellcome Open Research) was conducted to identify references published or available online through 27 March 2020 (Supplementary Table I ). The search strategy queried the terms ('non pharmaceutical intervention*' or 'nonpharmaceutical intervention*') or ('social distancing') in titles.

Screening, data extraction, qualitative synthesis, and quality assessment Two-reviewer screening of both titles/abstracts and full-texts was performed independently against a priori inclusion criteria (Supplementary Table II) , and conflicts were resolved with adjudication by a third reviewer. Inter-rater reliability (IRR) was determined by the kappa statistic. 9 Results were tracked in Microsoft Excel and EndNote ® . Data were abstracted into standardized forms for synthesis and thematic analysis. Systematic reviews with the same inclusion criteria were included and evidence was abstracted from the primary study for qualitative synthesis. Study quality was assessed by dual review using the Oxford levels of evidence (Table 1) . 10 

Meta-analyses were performed using a random-effects DerSimonian-Laird model 35 for proportions, using the inverse variance method with logit transformation to yield a pooled estimate and 95% confidence intervals (CIs) for attack rates. Separate analyses were conducted for 'no intervention', 'single intervention', and 'multiple interventions'. Between study heterogeneity was assessed using the τ 2 statistic. Statistical heterogeneity was also assessed using the I 2 statistic (range = 0% -100%), where higher values indicate a greater degree of variation. The I 2 statistic indicates the percentage of total variation that is attributable to study heterogeneity, rather than sampling error. Heterogeneity was tested using Cochran's Q statistic. Forest plots were produced to display study-specific and pooled attack rates, along with 95% CIs. The statistical significance level was set to 0.05. All analyses were conducted in R version 4.0.1 using the package Meta. 36, 37 

Literature searches identified 399 unique records from 434 references retrieved. Forty-three full-texts were reviewed (IRR = 89%), and 28 studies met inclusion criteria ( Figure 1 ).

Study characteristic are provided in Table 1 . The following results are reported as number of studies (n) and the corresponding percent of studies identified, for example, (n, %). The majority of included publications were modeling studies (24, 85%; Supplementary Tables III and IV) . [1] [2] [3] [4] [11] [12] [13] [14] 16, 17, 19, [21] [22] [23] [24] [26] [27] [28] [29] [30] [31] [32] [33] [34] The remaining studies were systematic reviews with similar inclusion criteria (2, 7%), 18 

• Immediate implementation occurred following an outbreak, and

• Attack rates were higher in children than in adults.

 School closure is insufficient as a single intervention in COVID-19 settings. 1 Combination of general social distancing NPIs including school closure, reducing community contacts, and implementing workplace policies with case isolation was most effective to decrease mean influenza attack rate. 26 

In influenza pandemics, only continuous and additive general social distancing NPIs (e.g. limit community contact, and invoking school closures and workplace policies) have comparable impact to combined intervention of fixed duration using general social distancing policies with provision of antiviral prophylaxis and treatment. 27 Substantial heterogeneity was noted in outcome measures employed to report each outcome, that is, disease incidence (e.g. infection rate or incident rate, incidence proportion or attack rate); disease transmission (e.g. R 0 , disease infectivity (I D ) factor), and disease mortality (e.g. case fatality proportion, peak excess death rates, and mortality rates).

c General social distancing (i.e. reduced interactions between potentially infectious individuals-but not diagnosed-in a broader community).

d Quarantine (i.e. involves the restriction of movement of presumably infectious individuals as they may have been exposed to disease).

e Isolation (i.e. separation of diagnosed individuals).

f Included suspected and undiagnosed cases. general infectious diseases. 16 The majority of studies were completely funded or funded in part by government agencies (21, 75%). 

Social distancing NPIs of interest included general social distancing (referred to as general), quarantine, and isolation (for intervention definition, see Supplementary Table III ; Figure 2 ). Social distancing NPIs were used as a single intervention (19, 68%) 1,3,11-13,16-22,24-26,31-34 and/or multiple interventions (24, 86%) [1] [2] [3] [4] [12] [13] [14] [15] [16] [17] [18] [20] [21] [22] 24, [26] [27] [28] [29] [30] [31] [32] [33] [34] with other NPIs and/or PIs including antiviral treatment and prophylaxis, and/or vaccination. Infectious viral disease outcomes were limited to disease incidence, transmission, and mortality ( Figure 3 , Supplementary Tables III and IV) .

Thematic analysis stratified results related to the effectiveness of general, isolation, and quarantine social distancing NPIs (Table 2 ). General social distancing was most frequently observed (27, 96%), [1] [2] [3] [4] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] with school closures identified as a common subtype (20, 71%). [1] [2] [3] [4] [11] [12] [13] [14] [15] [17] [18] [19] [20] [21] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] Other types of general social distancing identified included non-specific (7, 25%), 1, 13, 17, 26, 27, 30, 33 avoidance of contact, crowding, or mass gatherings (7, 25%), 1, 4, 18, 20, [31] [32] [33] workplace policies to limit contact (12, 43%), 4, 17, 18, 20, 23, [26] [27] [28] [29] [30] 32, 33 and travel restrictions (3, Figure 2 . Study intervention hierarchy for data analysis. This graphic visualizes the study details regarding data collection concerning interventions to mitigate or control viral pandemics or epidemics. Single (non-pharmaceutical interventions (NPIs) or pharmaceutical interventions (PIs)) interventions and/or multiple interventions with combinations of exclusive social distancing NPIs, social distancing NPIs plus other NPIs, social distancing NPIs plus PIs, and/or social distancing NPIs plus other NPIs and PIs.

Superscripts denote the labeling of specific interventions used to categorize study results provided in the data abstraction. 11%). 13, 15, 18 Isolation and quarantine were similarly identified (both: 16, 57%). [1] [2] [3] [4] [13] [14] [15] [16] [17] [18] [19] [20] 22, 26, [28] [29] [30] [31] 33, 34 Case isolation was identified in 13 studies (13, 46%) 2, 4, [14] [15] [16] 19, 20, 22, [29] [30] [31] 34 but only two studies (2, 7%) described hospitalization. 15, 18 Household quarantine (11, 39%) 2, 3, 4, 13, 18, 20, [28] [29] [30] [31] 34 was most common, with fewer studies examining other quarantine conditions, including border control (2, 7%), 18,15 geographic region by city or zone (1, 4%), 17 onboard (e.g. airline or ship) (1, 4%), 18 and voluntary self-protection (3, 11%). 1, 16, 18 If R 0 increased, then multiple NPIs' effectiveness on attack rate improved (R 0 = 1.5, − 29.3%; R 0 = 2.5, − 43.8%) at 3 weeks delay, but there was no relative change in attack rate if applied at 8 weeks. 26 Another combination of social distancing NPIs (e.g. general, quarantine, and isolation) plus a PI (e.g. antiviral treatment and prophylaxis) could decrease influenza attack rate by 39.5%-46.6% in a similar R 0 range with 60%-80% compliance. 4 School closure predicted age-specific reductions in percent cumulative attack rate comparing school-age children (21%-22%) to adults >53 years (40%) and adults <53 years (12%) by child-to-child community and household transmission. 25 Early implementation of school closure or generalized social distancing may result in better mitigation than the very early implementation of public travel restrictions. 13, 18 General social distancing plus quarantine and isolation NPIs substantially decreased 15 or predicted decrease 30,34 of COVID-19 R 0 (pre-intervention R 0 range = 1.28-6.2; postintervention R 0 range = 0.72 -3.22). 15, 30, 34 Governmentenforced isolation with monitored quarantine predicted that fewer general social distancing interventions were required to effectively lower R 0 in severe (R 0 >1.5) COVID-19 settings. 30 Timing and duration of school holidays played a critical role in limiting COVID-19 and influenza transmission rates in observational and modeling studies. 11, 15 Combinations of these general social distancing NPIs (e.g. changes in population behavior to limit public contact) with quarantine and isolation had a greater effect on decreasing COVID-19 transmissibility when the intervention duration was extended beyond holiday-related school closures (holiday only, 14% -15%; extension beyond holiday, 33% -44%). 15 A detailed summary of data abstraction for included studies is provided in Supplementary Table III .

All studies (28, 100%) reported some degree of effectiveness for each social distancing NPI examined across mild-tomoderate (R 0 <1.5) and/or moderate-to-severe (R 0 ⩾1.5) epidemics or pandemics based on provided R 0 (Figure 3) . Four studies 20,23,24,31 did not provide R 0 , and two studies 18, 25 had ranges of R 0 . Overall, combined social distancing NPIs were generally more effective in improving disease outcomes when compared to single interventions. Due to intervention heterogeneity and outcome reporting, it was generally not possible to provide valid head-to-head effectiveness comparisons across studies; however, a meta-analysis was conducted to examine the effect of social distancing NPIs on one outcome of interest, disease incidence.

Disease incidence was examined in 16 studies (57%) 1-4, 12,13,17-19,25-29,32,33 with primarily percent attack rate, and secondarily, infection rate reported (Figure 3 and Supplementary Table III ) and had mixed results when comparing the effectiveness of single versus combined NPIs.

Combining social distancing NPIs may be more effective in decreasing attack rate than single NPIs, in both COVID-19 and non-COVID-19 settings. 1, 3, 13, 26, 32 As shown in the Figure 3 . Summary of outcomes by study with respect to basic reproduction number (R 0 ) and quality assessment. The bubble plot lists included studies by year (y-axis) and outcome (x-axis; disease incidence, mortality, and/or disease transmission). The size of the circle represents the quality assessment provided by the corresponding Oxford Level of Evidence, 10 whereby smaller circles indicate low-quality (i.e. Level 3b or 4, case series) and larger circles denote moderate-quality (i.e. Level 2a, systematic review with homogeneity of 2b or better studies and Level 2b, modeling studies) evidence. The color of the circle represents the reproduction number (R 0 ) whereby blue indicates R 0 <1.5, purple denotes R 0 >1.5, turquoise represents studies with range of 1.5 > R 0 < 1.5 (both), white shows R 0 was not provided, and gray for systematic reviews that had a varied range of R 0 values. modeling studies, timeliness of and compliance with multiple interventions and the R 0 values may influence effectiveness. Delay in implementing multiple, general social distancing NPIs (e.g. workplace policies, school closure, and limiting group interactions) with case isolation is predicted to limit influenza attack rate change (week delay: three, −29.3%; eight, −14.3%) 18, 26 and would have similar effectiveness to earlier implemented single, general social distancing NPIs (3 weeks: range = −18.3% to −8.3%). 26 Modeling studies examining single social distancing NPIs' effectiveness suggest wide variation in general viral attack rate change (range = 0% -99%), and greater effects on influenza when the frequency of new cases remains low. 13 Simulation of influenza outbreaks revealed school closure was a common single NPI and may substantially lower attack rate (typically 20% -60%), 25 but had the highest impact when implemented in combination NPIs, 1 especially early in pandemics 25 and when continued for adequate duration. 27 The remaining general social distancing subtypes of mass gathering prohibitions, contact avoidance, and workplace policies to limit contact had similar effectiveness with a moderate (<20% decrease) effect on COVID-19 attack rate; 1 however, when used in combination NPIs, the impact was larger (>20% decrease). 1 Case isolation may be less effective than other single general social distancing NPIs on influenza attack rate, but changes in attack rate could improve with early implementation (3 weeks, −25.3%; 8 weeks, −8.3%). 18 A meta-analysis was conducted on six studies 3,12,13,19,26,27 that reported influenza attack rates and the population at-risk for both no intervention and social distancing NPIs as a proxy (Supplementary material, Figures I and II) . Some studies provided attack rate estimates assuming different model parameters (e.g. R 0 ) and interventions (Supplementary material, Figure II) . Attack rates for no intervention ranged from 10% to 73% and the pooled attack rate was 42% (95% CI = 30% -55%) with significant heterogeneity (p < 0.0001). Ranges of attack rates varied greatly for social distancing NPIs (single NPIs, 6% -65%; multiple NPIs, 4% -73%). The pooled attack rate for single NPIs and multiple NPIs was 29% (95% CI = 23% -36%) and 22% (95% CI = 16% -29%), respectively, with significant heterogeneity (p < 0.0001). The random-effects model demonstrated substantial statistical heterogeneity (I 2 = 100%) ensuing from various possible resources within each analysis, such as different modeling methods, different parameters for the simulations, and R 0 values.

Disease transmission was examined in 15 (54%) studies 3, 11, [15] [16] [17] [18] [20] [21] [22] [23] [24] [25] 30, 33, 34 as percent or effective decrease in R 0 , or scaled disease infectivity (I D ) factor as a proxy for transmissibility ( Figure 3) . A few studies examined single NPIs, predicting decreased influenza transmission following school closures (range = 14%-100%), 11, 17, 21 household quarantine (20%), 18 and vaccination (15%). 24 Modeling of case isolation predicted decreases in COVID-19 effective R 0 from 1.5 to 1.25 and 2.5 to 2.1. 22 Generally, combinations of social distancing NPIs predicted 18, 24 or changed 18,20 viral transmissibility in both COVID-19 and non-COVID-19 settings (range = −14% to −54%), 18,15,24 but compliance affected their success. One modeling study noted that there was greater than 90% probability of obtaining 0% influenza transmission rates with a combination of general social distancing NPIs; 90% achievement with socially targeted antiviral treatment and prophylaxis and 80% with reduced movement in affected zones following geographic targeting of quarantine interventions. 17 Isolation 15, 17, 18, 22, 30, 34 and quarantine 16, 18, 30 are both effective in limiting influenza and COVID-19 disease transmission when used in combination NPIs. Modeling of isolation combined with contact tracing decreased COVID-19 transmission (pre-intervention R 0 , 1.5; post-intervention R 0 , 0.5 -0.9 based on 20% -100% contact tracing achievement). 22 This study noted the delay between symptom onset and isolation had the largest role in determining whether a COVID-19 outbreak (R 0 = 1.5) was controllable, and higher achievement of contact tracing was required as R 0 increased. 22 However, the effectiveness of quarantine on general viral disease could be increased when general social distancing interventions are combined. 16, 17 Risk of secondary influenza transmission decreased when quarantine (adjusted odds ratio (OR) = 1.25; 95% CI = 1.06 -1.47; p = 0.0008) was combined with antiviral prophylaxis and treatment (adjusted OR = 0.042; 95% CI = 0.004 -0.434; p = 0.0008) in simulation. 18 Intervention timing influenced NPI effectiveness on limiting transmission. Early and short-term (e.g. 3 months) general social distancing NPIs could delay the timing of peak infections by as much as 7 months, but would have a modest impact on COVID-19 transmission. 33 Modeling effectiveness of workplace policies improved with increasing I D , as adult contacts contribute largely to influenza transmission. 3 In addition, mask wearing and handwashing, combined with social distancing NPIs, limited COVID-19 and influenza transmissibility in both observational and modeling studies. 18, 15 Mortality Mortality was examined in 10 studies (36%) 1, 3, 14, 18, 20, 21, 25, 28, 31, 34 as were case fatality proportion, mortality rate, peak excess death rate, and total deaths (i.e. all-cause mortality) (Figure 3 ). Single and multiple social distancing NPI modeling had large variability on influenza-related mortality rate (ranges of single: range = 3% -78%; multiple = 6% -97%). 31 A COVID-19 modeling study determined mortality could be further decreased by 34%-49% by adding age-dependent (>70 years) general social distancing interventions to quarantine and isolation. 1 However, general social distancing NPIs plus PIs could further lessen mortality in predictive models; using general social distancing NPIs, influenza-related mortality could be decreased by 93%, but by providing antiviral prophylaxis and treatment (e.g. adamantanes and neuraminidase inhibitors) to 2% of the affected region, mortality could be decreased by 97%. 3 The number of general social distancing NPIs was associated with lower peak excess influenza death rates (0.002 > p < 0.047), 20 whereby more interventions predicted lower death rates.

Temporal relationships with mortality were similarly identified whereby duration and timing impacted the effectiveness of social distancing NPIs. Influenza-related mortality could be further decreased by extending intervention durations; 14,31 one modeling study noted that a substantial decrease in mortality could be obtained by extending a combination of NPIs (e.g. general social distancing, handwashing, mask wearing, and case isolation) by 5 months (no extension, 6% -43%; with extension, 38% -92%). 14 Quarantine by controlling movement within infected geographies with lower R 0 (e.g. R 0 >1) predicted lower excess influenza death rates. 18 A model predicted that earlier epicenter lockdown would have reduced the number COVID-19 deaths overall (up to 99.3%), but would increase the number of deaths in the epicenter. 34 Moreover when added to general social distancing and personal preventive measures (e.g. handwashing and mask wearing), quarantine would reduce the influenza mortality rate by 63%. 28 Case isolation had mixed effects on influenza-related mortality; 17,20 however, total mortality burden was predicted to be lower when isolation was used early (p = 0.008) and with increased duration (p = 0.005), in combination with quarantine and general social distancing NPIs. 18 Similarly, early implemented general social distancing NPIs predicted lower peak excess influenza death rates. 20 Late interventions, regardless of duration or type of intervention, had worse predicted mortality-related outcomes in influenza outbreaks. 31 

Using Oxford levels of evidence, 10 two (7%) studies provided Level 2a evidence; 18,25 22 (79%) studies were assessed as Level 2b; [1] [2] [3] [4] [11] [12] [13] [14] [15] [16] [17] 19, [21] [22] [23] [24] [26] [27] [28] [29] 32, 33 three (7%) were Level 3b; 30, 31, 34 and one (4%) 20 provided Level 4 evidence. The quality of the evidence is moderate as the majority of studies were Level 2 quality (descriptions in Table 1 and Figure 3 ).

NPIs are important public health measures, implemented either as a single measure or in combination with other NPIs, to help decrease incidence, transmission, and mortality of viral and other infectious diseases. Early, sustained, and combined application of various NPIs could mitigate and control primary outbreaks and prevent more severe secondary or tertiary outbreaks, 20,24,34 provided decision-makers consider dynamic R 0 values, the propensity of getting infected among certain high-risk groups (e.g. increasing age and underlying comorbidities), and asymptomatic cases that may be as infectious as symptomatic patients.

Retrospective observational and modeling studies suggest the effectiveness of social distancing NPIs depends on disease severity as well as intervention timing and adherence (e.g. implementation delays, duration, and population compliance/coverage). Thus, an outbreak could be effectively suppressed through strict and early implementation of an intervention (single or in combination) for a pre-determined duration. The more widespread the infectious disease and/or the longer the delay in implementation of a measure, the more limited the effectiveness of the intervention. 3, 12, 17, 18, 26, 33 Effective mitigation requires combined social distancing interventions (e.g. school closure, quarantine, or isolation), supplemented by other NPIs (e.g. mask wearing and handwashing) and PIs (e.g. antiviral treatment and/or vaccinations). Several studies suggested that multiple interventions are more effective than a single intervention. 1, 16, 18, 29, 30 Timely and continuous but evolving adoption of evidence-based social distancing strategies could substantially mitigate and control the pandemic until an efficacious treatment and or/ matched vaccine become available. 28, 33 The majority of included studies implemented modeling to predict the effects of social distancing NPIs on viral disease outbreaks. Further work is needed to model case fatality rates, mortality, and costs, and to predict disease transmission, effects of differing vaccination rates, and case severity and their correlation with NPIs.

This study provides both qualitative and quantitative evidence related to the implications of using NPIs to contain infectious diseases, mostly from past studies, supported by current experiences. Public health policy makers, educators, clinicians, and researchers could better understand the factors that could facilitate more favorable outcomes resulting from implementations of NPIs. These include matching the right intervention type to specific community circumstances such as the stage of the curve or type of venue (school closures, mass gathering cancelations, contact tracing, etc.) and/ or strategizing implementation time, duration, and intensity (early, prolonged and strict lock down, prioritization of protecting the high-risk patient population first, for example, elderly having other comorbidities).

To our knowledge, this is a novel review employing a rapid methodology to provide both qualitative and quantitative synthesis of the evidence related to the effects of social distancing NPIs on respiratory viral disease outcomes including incidence, transmission, and mortality. Our results should be interpreted in the context of the limitations of this study. Studies with a search cutoff of 27 March 2020 were limited from online searches of MEDLINE, Google Scholar, and pre-print databases. In addition, more relevant studies may be identified from other databases and those published after the search cutoff date. Handsearching of included studies or conference proceedings was not performed. In addition, articles were limited to English language with an abstract. Metaanalyses were limited to influenza attack rate and results had high statistical heterogeneity. These quantitative findings conflict with the narrative results relating to the effectiveness of single versus combined NPIs on disease incidence. Potential explanations could be the high study heterogeneity (i.e. different models, varying parameters for the models, variable R 0 , and different compliance) and a limited number of studies each of the analyses. Because of the limited number of studies, meta regression analysis with multiple covariates was not recommended. Despite these limitations, the visual representations derived from the meta-analysis provide insights into attack rate comparisons by type of intervention (e.g. none, single, and combined). Confounders such as weather changes (e.g. temperature and humidity levels) were not considered. In addition, a large number of modeling studies were used to derive this evidence as opposed to epidemiological findings. This evidence can facilitate decisionmaking to better recognize and implement measures that support mitigation and suppression of viral infectious disease during outbreaks, and successful NPIs can provide time for the development and evaluation of effective treatments and vaccines.

This review provides evidence that a proper deployment of strategically combined social distancing NPIs as a public health measure, along with other non-pharmaceutical and PIs, could mitigate and control disease by decreasing viral disease incidence, transmission, and mortality.

Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand

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Non-pharmaceutical interventions used for COVID-19 had a major impact on reducing influenza in China in 2020

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The authors thank Winnie Felix and Courtney VanHouten for helping with searching for relevant papers, and Dr Van C. Willis for his critical reading and support for the completion of the revisions.

All supporting data has been provided in additional files.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research study was supported by IBM ® Watson Health ® (no grant number to disclose).

Rubina F Rizvi https://orcid.org/0000-0001-9432-3086

Supplemental material for this article is available online.