Measures to reduce the spread of COVID-19 through non-pharmaceutical interventions (NPIs) such as mask wearing and social distancing are a key tool in combatting the impact of the ongoing coronavirus pandemic.
These actions also have greatly reduced incidence of many other diseases, including influenza and respiratory syncytial virus (RSV).
Current reductions in these common respiratory infections, however, may merely postpone the incidence of future outbreaks, according to a study by Princeton University researchers published Nov. 9 in the Proceedings of the National Academy of Sciences.
“Declines in case numbers of several respiratory pathogens have been observed recently in many global locations,” said first author Rachel Baker, an associate research scholar at the High Meadows Environmental Institute (HMEI) at Princeton University.
“While this reduction in cases could be interpreted as a positive side effect of COVID-19 prevention, the reality is much more complex,” Baker said.
“Our results suggest that susceptibility to these other diseases, such as RSV and flu, could increase while NPIs are in place, resulting in large outbreaks when they begin circulating again.”
Baker and her co-authors found that NPIs could lead to a future uptick in RSV – an endemic viral infection in the United States and a leading cause of lower respiratory-tract infections in young infants -but that the same effect was not as pronounced for influenza.
“Although the detailed trajectory of both RSV and influenza in the coming years will be complex, there are clear and overarching trends that emerge when one focuses on some essential effects of NPIs and seasonality on disease dynamics,” said co-author Gabriel Vecchi, Princeton professor of geosciences and the High Meadows Environmental Institute.
The researchers used an epidemiological model based on historic RSV data and observations of the recent decline in RSV cases to examine the possible impact of COVID-19 NPIs on future RSV outbreaks in the United States and Mexico.
They found that even relatively short periods of NPI measures could lead to large future RSV outbreaks. These outbreaks were often delayed following the end of the NPI period, with peak cases projected to occur in many locations in winter 2021-22.
“It is very important to prepare for this possible future outbreak risk and to pay attention to the full gamut of infections impacted by COVID-19 NPIs,” Baker said.
The authors also considered the implications of COVID-19 NPIs for seasonal influenza outbreaks and found results qualitatively similar to RSV. The dynamics of influenza are much harder to project due to viral evolution, however, which drives uncertainty over future circulating strains and the efficacy of available vaccines.
“For influenza, vaccines could make a big difference,” Baker said. “In addition, the impact of NPIs on influenza evolution is unclear but potentially very important.”
“The decrease in cases of influenza and RSV – as well as the possible future increase we project – is arguably the broadest global impact of NPIs across a variety of human diseases that we’ve seen,” said co-author Bryan Grenfell, the Kathryn Briger and Sarah Fenton Professor of Ecology and Evolutionary Biology and Public Affairs, who is associated faculty in HMEI.
“NPIs could have unintended longer-term impacts on the dynamics of other diseases that are similar to the impact on susceptibility we projected for RSV,” he said.
A similar effect of pandemic-related NPIs on other pathogens was observed following the 1918 influenza pandemic. Historic measles data from London show a shift from annual cycles to biennial outbreaks following a period of control measures implemented at that time.
Co-author C. Jessica Metcalf, associate professor of ecology and evolutionary biology and public affairs and an associated faculty member in HMEI, said that directly evaluating the associated risks of NPIs by developing and deploying tools such as serology that would better measure susceptibility is an important public health and policy direction.
“The future repercussions of NPIs revealed by this paper hinge on how these measures change the landscape of immunity and susceptibility,” Metcalf said.
The paper, “The impact of COVID-19 non-pharmaceutical interventions on the future dynamics of endemic infections” was published online Nov. 9 by the Proceedings of the National Academy of Sciences.
A total of 415 sites (i.e. 235 cities from 10 countries and 180 countries) were included in this study. Table S2 summarises the relevant information on COVID-19 and the NPIs implemented in the 190 countries during the study period. As of 13 April 2020, 1,908,197 cases of COVID-19 infection were reported. The highest number of cases was reported in the United States of America [577,165 (30.25% of the total number of cases reported worldwide)], followed by Spain, Italy, France, Germany, the United Kingdom, China, Iran, Turkey and Belgium.
Table 1 shows the data pertaining to the implementation of NPIs at the study sites over the study period. No official NPIs were ever implemented in 382 sites. In many sites, two or more types of NPIs were ever implemented simultaneously during the study period. The common types of NPIs or combinations of NPI types that were implemented across the sites were ‘traffic only’ (138 sites), ‘traffic + quarantine’ (130 sites), ‘traffic + distancing’ (177 sites), and ‘traffic + distancing + quarantine’ (218 sites).
The implementation durations of each type of NPI or each combination of NPI types ranged from 4 to 38 days. Relatively long median durations of implementation were observed for ‘traffic only’ (12.5 days), ‘distancing + mandatory mask’ (16 days), ‘traffic + quarantine’ (33 days), ‘traffic + distancing’ (19 days), ‘traffic + quarantine + mandatory mask’ (38 days), ‘traffic + distancing + quarantine’ (24 days) and ‘traffic + distancing + quarantine + mandatory mask’ (37 days).
Table 1 – Non-pharmaceutical interventions implemented in the 190 countries between 23 January 2020 and 13 April 2020 (N = 415).
| Type of NPIs | No. of sites that ever implemented the NPIs (%) | Median duration (range) of NPI implementation (days) |
|---|---|---|
| 0 NPIs | 382 (92.05%) | N/A |
| Any one type of NPI | ||
| Mandatory mask only | 1 (0.24%) | 4 (N/A) |
| Quarantine only | 48 (11.57%) | 7 (1-53) |
| Distancing only | 40 (9.64%) | 4 (1-31) |
| Traffic only | 138 (33.25%) | 12.5 (1-75) |
| Any two types of NPIs | ||
| Distancing + mandatory mask | 1 (0.24%) | 16 (N/A) |
| Distancing + quarantine | 21 (5.06%) | 6 (1-35) |
| Traffic + mandatory mask | 1 (0.24%) | 4 (N/A) |
| Traffic + quarantine | 130 (31.33%) | 33 (1-72) |
| Traffic + distancing | 177 (42.65%) | 19 (1-38) |
| Quarantine + mandatory mask | 0 (0.00%) | N/A |
| Any three types of NPIs | ||
| Distancing + quarantine + mandatory mask | 2 (0.48%) | 8.5 (1-16) |
| Traffic + quarantine + mandatory mask | 36 (8.67%) | 38 (2-42) |
| Traffic + distancing + mandatory mask | 1 (0.24%) | 7 (N/A) |
| Traffic + distancing + quarantine | 218 (52.53%) | 24 (2-49) |
| All four types of NPIs | ||
| Traffic + distancing + quarantine + mandatory mask | 60 (14.46%) | 37 (1-75) |
NPIs: Non-pharmaceutical Interventions
%: Percentage of sites implementing corresponding types of NPI among the 415 included sites.
N/A: not applicable
Table 2 presents the associations between each type of NPI and the Rt of COVID-19. The implementations of any type of NPI were significantly associated with a decrease in the Rt of COVID-19. Mutual adjustments substantially diluted these associations. The implementations of mandatory mask, quarantine, distancing and traffic were associated with changes of -15.14% (-21.79% to -7.93%), -11.40% (-13.66% to -9.07%), -42.94% (-44.24% to -41.60%) and -9.26% (-11.46% to -7.01%) in the Rt of COVID-19, respectively, compared with the Rt in the sites without the implementation of the corresponding measures.
Table 2 – Associations of individual type of non-pharmaceutical intervention with the Rt of COVID-19
| Type of NPI | Model 1 | Model 2 | |||
|---|---|---|---|---|---|
| Difference (95%CI) | P | Difference (95%CI) | P | ||
| Mandatory mask (Yes vs. No) | -33.35% (-39.07 to -27.09) | <0.001 | -15.14% (-21.79 to -7.93) | <0.001 | |
| Quarantine (Yes vs. No) | -32.98% (-34.59 to -31.33) | <0.001 | -11.40% (-13.66 to -9.07) | <0.001 | |
| Distancing (Yes vs. No) | -46.46% (-47.63 to -45.27) | <0.001 | -42.94% (-44.24 to -41.60) | <0.001 | |
| Traffic (Yes vs. No) | -29.09% (-30.73 to -27.42) | <0.001 | -9.26% (-11.46 to -7.01) | <0.001 |
NPIs: Non-pharmaceutical Interventions
Sites without the corresponding type of NPI as the reference.
Results are presented as percentage differences in the Rt with [95% Confidence Interval (CI)].
Model 1: Adjusted for the calendar time, Rt on the previous day, public health response time defined as the time in days between the activation of the first NPI and the date of reporting of the first case, an indicator of the day of the week and public holidays, implementation duration of NPIs, population density, median age, and GHSI.
Model 2: Further mutually adjusted for the other three types of NPIs, for example, adjusted for quarantine, distancing and traffic in the model for the association between ‘mandatory mask’ type of NPI and Rt.
Table 3 shows the comparisons of the effectiveness of different NPIs on the Rt of COVID-19. ‘Distancing only’ led to a greater decrease in the Rt of COVID-19 than ‘traffic only’ and ‘quarantine only’. The combinations of other types of NPIs with distancing were generally associated with a greater decrease in the Rt compared with the combinations without distancing. The combinations with more types of NPIs were generally associated with a greater decrease in the Rt. No significant associations were observed for ‘mandatory mask only’, ‘distancing + mandatory mask’, ‘traffic + mandatory mask’, and ‘traffic + distancing + mandatory mask’.
Table 3 – Comparison of effectiveness of different NPI types or combinations on the Rt of COVID-19.
| Type of NPIs | Difference (95%CI) | P |
|---|---|---|
| Any one type of NPIs | ||
| Mandatory mask only | -34.06% (-60.78 to 10.87) | 0.116 |
| Quarantine only | -10.6% (-15.31 to -5.64) | <0.001 |
| Distancing only | -23.03% (-28.43 to -17.22) | <0.001 |
| Traffic only | -9.64% (-12.21 to -7.00) | <0.001 |
| Any two types of NPIs | ||
| Distancing + mandatory mask | 53.30% (-2.50 to 141.03) | 0.064 |
| Distancing + quarantine | -38.58% (-44.23 to -32.37) | <0.001 |
| Traffic + mandatory mask | -66.58% (-92.67 to 52.41) | 0.157 |
| Traffic + quarantine | -17.83% (-20.07 to -15.53) | <0.001 |
| Traffic + distancing | -44.11% (-46.37 to -41.76) | <0.001 |
| Any three types of NPIs | ||
| Distancing + quarantine + mandatory mask | -69.73% (-82.48 to -47.69) | <0.001 |
| Traffic + quarantine + mandatory mask | -17.06% (-24.99 to -8.29) | <0.001 |
| Traffic + distancing + mandatory mask | -54.32% (-79.59 to 2.24) | 0.057 |
| Traffic + distancing + quarantine | -54.12% (-55.63 to -52.56) | <0.001 |
| All four types of NPIs | ||
| Traffic + distancing + quarantine + mandatory mask | -62.81% (-66.27 to -58.98) | <0.001 |
NPIs: Non-pharmaceutical Interventions
Sites with No NPI implementation are the reference.
Results are presented as percentage differences in the Rt with [95% Confidence Interval(CI)]
Adjusted for calendar time, Rt on the previous day, public health response time defined as the number of days between the date of activation of the first NPI and the date of reporting of the first case, an indicator of the day of the week and public holidays, implementation duration of a type of NPI, population density, median age and GHSI.
As shown in Table 4 , subgroup data analysis generally yielded similar results. The association strengths differed slightly for some subgroups, that is, greater decreases in the Rt were observed for the subgroups of ‘higher population density’ and ‘lower GHSI’. No significant associations were observed for some subgroups.
Table 4 – Subgroup analysis of association between non-pharmaceutical Interventions and the Rt of COVID-19 transmission
| Types of NPIs | Subgroup analysis | |||
|---|---|---|---|---|
| Stratified by continents | ||||
| European | American | Asia | African | |
| Comparison of individual types of NPIsa | ||||
| Mandatory mask (Yes vs. No) | -1.33% (-13.02 to 11.94) | -23.68% (-41.5 to -0.45) | -0.26% (-6.15 to 6.01) | -28.56% (-48.8 to -0.31) |
| Quarantine (Yes vs. No) | -18.27% (-22.14 to -14.21) | -4.23% (-10.07 to 1.99) | -4.55% (-8.47 to -0.46) | -10.72% (-16.04 to -5.07) |
| Distancing (Yes vs. No) | -39.4% (-42.07 to -36.59) | -42.87% (-45.37 to -40.27) | -17.76% (-20.56 to -14.85) | -16.05% (-21.33 to -10.41) |
| Traffic (Yes vs. No) | -11.26% (-15.18 to -7.17) | -8.34% (-13.75 to -2.58) | -8.62% (-11.95 to -5.17) | -30.86% (-34.83 to -26.66) |
| Comparison of combinations of NPI typesb | ||||
| Any one type of NPI | ||||
| Mandatory mask only | -41.49% (-65.82 to 0.16) | N/A | N/A | N/A |
| Quarantine only | -20.21% (-27.00 to -12.79) | 0.84% (-10.00 to 12.98) | -11.62% (-18.83 to -3.76) | -4.01% (-15.45 to 8.97) |
| Distancing only | -38.35% (-45.64 to -30.09) | -33.33% (-42.93 to -22.12) | -18.8% (-30.30 to -5.41) | 11.55% (-3.32 to 28.71) |
| Traffic only | -9.21% (-13.65 to -4.54) | -15.12% (-22.68 to -6.81) | -12.58% (-16.2 to -8.81) | -24.60% (-30.13 to -18.62) |
| Any two types of NPIs | ||||
| Distancing + mandatory mask | N/A | N/A | 7.27% (-26.61 to 56.77) | N/A |
| Distancing + quarantine | -48.75% (-56.37 to -39.80) | -50.46% (-63.40 to -32.95) | -20.51% (-34.83 to -3.06) | -15.48% (-26.91 to -2.27) |
| Traffic + mandatory mask | N/A | N/A | N/A | -74.36% (-96.01 to 64.91) |
| Traffic + quarantine | -42.60% (-48.81 to -35.65) | -11.70% (-15.46 to -7.78) | -9.24% (-13.91 to -4.31) | -34.84% (-40.35 to -28.83) |
| Traffic + distancing | -49.10% (-52.82 to -45.08) | -38.73% (-44.72 to -32.1) | -17.13% (-22.00 to -11.96) | -41.59% (-46.93 to -35.71) |
| Any three types of NPIs | ||||
| Distancing + quarantine + mandatory mask | 14.41% (-34.75 to 100.60) | N/A | -41.40% (-66.30 to1.90) | N/A |
| Traffic + quarantine + mandatory mask | -35.98% (-56.39 to -6.02) | -31.04% (-74.06 to 83.34) | -5.07% (-11.73 to 2.09) | N/A |
| Traffic + distancing + mandatory mask | N/A | N/A | -28.19% (-64.91 to 46.93) | N/A |
| Traffic + distancing + quarantine | -55.24% (-58.04 to -52.26) | -50.94% (-53.41 to -48.34) | -26.66% (-31.42 to -21.55) | -48.26% (-53.16 to -42.85) |
| All four types of NPIs | ||||
| Traffic + distancing + quarantine + mandatory mask | -54.03% (-60.16 to -46.94) | -62.40% (-71.60 to -50.24) | -30.90% (-35.65 to -25.79) | -57.91% (-69.86 to -41.21) |
| Stratified by population density | Stratified by GHSI | |||
| ≤ 110.5 pears/km2 | > 110.5 pears/km2 | ≤ 58.5 | >58.5 | |
| Comparison of individual types of NPIsa | ||||
| Mandatory mask (Yes vs. No) | 0.33% (-8.71 to 10.26) | -24.22% (-33.10 to -14.16) | -24.64% (-30.01 to -18.86) | -17.85% (-41.76 to 15.88) |
| Quarantine (Yes vs. No) | -8.09% (-11.03 to -5.06) | -20.38% (-23.80 to -16.80) | -22.16% (-24.61 to -19.63) | 21.06% (14.22 to 28.31) |
| Distancing (Yes vs. No) | -42.58% (-44.30 to -40.80) | -43.00% (-45.01 to -40.91) | -41.40% (-43.1 to -39.64) | -39.37% (-41.82 to -36.82) |
| Traffic (Yes vs. No) | -11.46% (-14.05 to -8.79) | -3.93% (-8.04 to 0.36) | -13.32% (-15.8 to -10.77) | -27.64% (-32.22 to -22.75) |
| Comparison of combinations of NPIb | ||||
| Any one type of NPI | ||||
| Mandatory mask only | -32.62% (-60.74 to 15.66) | N/A | -40.27% (-64.91 to 1.68) | N/A |
| Quarantine only | 2.11% (-4.02 to 8.64) | -35.8% (-41.93 to -29.01) | -27.97% (-32.60 to -23.02) | 30.17% (20.21 to 40.96) |
| Distancing only | -17.39% (-26.00 to -7.77) | -30.13% (-36.64 to -22.96) | -32.09% (-37.69 to -25.99) | -8.65% (-21.22 to 5.93) |
| Traffic only | -11.61% (-14.64 to -8.49) | -5.10% (-10.11 to 0.18) | -12.86% (-15.64 to -10.00) | -26.96% (-33.39 to -19.91) |
| Any two types of NPIs | ||||
| Distancing + mandatory mask | N/A | 40.99% (-10.17 to 121.29) | 21.86% (-21.3 to 88.7) | N/A |
| Distancing + quarantine | -34.91% (-44.27 to -23.98) | -41.29% (-48.06 to -33.64) | -46.29% (-51.7 to -40.27) | -31.53% (-49.42 to -7.32) |
| Traffic + mandatory mask | -68.2% (-94.53 to 84.7) | N/A | -70.57% (-93.53 to 33.82) | N/A |
| Traffic + quarantine | -18.25% (-20.99 to -15.42) | -21.94% (-25.62 to -18.08) | -30.81% (-33.99 to -27.48) | -10.56% (-14.78 to -6.13) |
| Traffic + sdistancing | -40.23% (-43.34 to -36.94) | -47.4% (-50.75 to -43.82) | -48.01% (-50.53 to -45.37) | -44.41% (-49.82 to -38.43) |
| Any three types of NPIs | ||||
| Distancing + quarantine + mandatory mask | 37.89% (-20.47 to 139.08) | -81.93% (-90.65 to -65.08) | -79.01% (-88.57 to -61.46) | N/A |
| Traffic + quarantine + mandatory mask | 6.79% (-5.37 to 20.51) | -38.47% (-46.73 to -28.93) | -42.60% (-47.41 to -37.35) | -7.17% (-63.86 to 138.44) |
| Traffic + distancing + mandatory mask | -52.9% (-79.49 to 8.13) | N/A | -59.44% (-81.96 to -8.79) | N/A |
| Traffic + distancing + quarantine | -53.76% (-55.64 to -51.8) | -55.27% (-57.74 to -52.65) | -58.75% (-60.70 to -56.69) | -48.26% (-50.58 to -45.82) |
| All four types of NPIs | ||||
| Traffic + distancing + quarantine + mandatory mask | -54.29% (-59.07 to -48.96) | -71.21% (-75.22 to -66.54) | -72.36% (-74.83 to -69.65) | -56.94% (-70.12 to -37.95) |
N/A: not applicable due to no sites implemented the corresponding type of NPIs
Results are presented as percentage differences in the Rt with [95% Confidence Interval (CI)]aSites without the corresponding type of NPI as the reference. Adjusted for calendar time, Rt on the previous day, public health response time defined as the number of days between the date of activation of the first NPI and the date of reporting of the first case, an indicator of day of the week and public holidays, implementation duration of a type of NPI, population density, median age and GHSI, and mutually adjusted for the other three types of NPIs, for example, adjusted for quarantine, distancing and traffic in the model for the association between the ‘mandatory mask’ type of NPI and Rt.bSites with No NPI implementation are the reference. Adjusted for calendar time, Rt on the previous day, public health response time defined as the number of days between the date of activation of the first NPI and the date of reporting of the first case, an indicator of the day of the week and public holidays, implementation duration of a type of NPI, population density, median age and GHSI.
Tables S3-S5 summarise the results of our sensitivity analyses. The decreased magnitudes in the Rts were generally smaller on days Lag 3, Lag 7 and Lag 14 compared with those on the current day (Table S3). Similar results were obtained by excluding the outlier province (Hubei, China) (Table S4), and by adjusting for percentages of aged≥65 years instead of median age (Table S5).
Discussion
This comprehensive ecological study covering 190 countries indicated that the implementation of any type of NPI, namely traffic, distancing, mandatory mask or quarantine, was significantly associated with a decrease in the Rt of COVID-19. All NPI implementations involving distancing were associated with a greater decrease in the Rt of COVID-19 than those not involving distancing. Accordingly, combinations with more types of NPIs seemed to be associated with a greater decrease in the Rt of COVID-19.
Most previous studies have investigated the effectiveness of a single NPI rather than a group of NPIs despite the fact that two or more NPIs are commonly implemented simultaneously (Auger et al., 2020, Chinazzi et al., 2020, Hernandez et al., 2020, Milne and Xie, 2020). The results of our study were consistent with those of the studies that concluded that the implementation of NPIs was associated with a decrease in transmissibility, such as the studies in mainland China showing that travel restrictions might delay the progression of the COVID-19 epidemic by 3–5 days (Chinazzi et al., 2020, Tian et al., 2020) and the study in New York showing that wearing a mask could reduce daily deaths by 17%–45% over 2 months (Eikenberry et al., 2020).
Moreover, two studies reported social distancing to be an effective NPI (Hernandez et al., 2020, Zhang et al., 2020). A study conducted in China showed that social distancing and epicentre lockdown might reduce the number of new infection cases by up to 98.9% (Zhang et al., 2020), while another study indicated that social distancing reduced the growth rate of confirmed cases in five countries (Austria, Belgium, Italy, Malaysia and South Korea) by 52.37% on average (SD 13.37%) (Hernandez et al., 2020). A few studies investigated the effectiveness of multiple NPIs in China (Cowling et al., 2020, Lai et al., 2020, Milne and Xie, 2020, Pan et al., 2020), Europe countries (Flaxman et al., 2020), the United Kingdom (Davies et al., 2020), and Singapore (Koo et al., 2020).
Their results showed that the implementation of multiple NPIs was associated with a reduction in the transmission of COVID-19. In contrast, a study conducted in 20 European countries revealed that stay-at-home orders, closure of all non-essential businesses and wearing of face masks in public were not significantly associated with the incidence rate of confirmed cases (Hunter et al., 2020).
It is difficult to directly compare the results of our study with those of previous studies owing to multiple reasons, such as differences in study design and period, targeted populations and transmissibility parameters. Moreover, most previous studies used modelling methods to simulate the epidemic with the implementation of NPIs.
In contrast, we used the data published on the official webpages of the governments of 190 countries to provide direct evidence about the effectiveness of NPI implementation on COVID-19 transmission. Nevertheless, our study and most previous studies support the implementation of NPIs as a measure for containing the global pandemic of COVID-19.
Few studies have compared the effectiveness of different NPIs and their combinations for containing COVID-19. Our results showed that the NPI of distancing and its combinations with other NPI types are associated with a greater decrease in the Rt of COVID-19, suggesting that distancing should be adopted as a priority NPI for COVID-19 containment. This is in line with a modelling study in China, which also suggested that social distancing seemed to have a greater impact on the containment of COVID-19 outbreak than travel restrictions (Lai et al., 2020). Moreover, our study indicated that the simultaneous implementation of two or more NPI types seems to be associated with a greater decrease in the Rt of COVID-19.
In the comparisons of the effectiveness of different NPIs and their combinations, we found nonsignificant associations for ‘mandatory mask only’ and the combinations ‘distancing + mandatory mask’, ‘traffic + mandatory mask’, and ‘traffic + distancing + mandatory mask’ (Table 3). Nonsignificant associations were also found in some subgroup analyses (Table 4), which were inconsistent with previous studies reporting that face mask was associated with reduced risk of COVID-19 infection (Cheng et al., 2020, Chu et al., 2020, Eikenberry et al., 2020). The lack of statistical significance for these associations in our study may be ascribed to the small number of cities or countries that implemented the above NPI types and combinations.
Our study has several important strengths. First, we captured the available data on confirmed cases of COVID-19 infection and legal NPIs implemented from 190 countries, which suggests that our findings are applicable in most countries worldwide. The large sample size allowed us to obtain more stable estimates and conduct a series of subgroup and sensitivity analyses, which generally yielded similar results, indicating that the associations observed in our study are robust.
Second, we adjusted for a series of important confounders in the model, including socio-demographics and health-security capacities. Finally, this study is the first to present a comprehensive and quantitative comparison of the effectiveness of various NPIs and their combinations at a global scale, which may provide timely evidence for policymakers to adopt appropriate NPIs in different countries to control the outbreak of COVID-19.
Several limitations should be noted. First, we treated an NPI as ‘on’ in the data analysis if the NPI was officially announced as being in force by a government. We were unable to account for the intensity of enforcement and people’s compliance, which might have varied across countries and cities.
Also, contents of each NPI at different sties might be somewhat different. However, we included a city-level random intercept that may control the between-city variations in intensity and compliance. Second, we considered four types of NPIs that were legally and officially announced by the governments of countries and cities considered in this study.
A few NPIs, such as knowledge promotion, voluntary isolation, and voluntary wearing a mask were not considered. Moreover, some cultural factors, such as personal hygiene, social habits and family size, may influence the spread of COVID-19. Further investigations are warranted to assess the effects of these factors. Third, the information of testing capacities in each site was not available. However, we already adjusted for GHSI which is an important indicator reflecting testing capacity.
Forth, although our results shows non-significant associations of Rt with ‘mandatory mask only’ and the combinations ‘distancing + mandatory mask’, ‘traffic + mandatory mask’, and ‘traffic + distancing + mandatory mask’, we should interpret with cautions because these estimates came from only a few sites. Fifth, because all the cities or countries took action to separate infected persons from uninfected persons at the outset, the effects of not separating infected persons remains unknown.
Additionally, the effects of different NPIs may be highly correlated, because they commonly synchronously occurred and were jointly implemented, which may contradict the assumption of independent covariates in GLMM model. However, the results could also be affected by other NPIs if only one type of NPIs was considered. Thus, we gradually introduced two models and presented them separately in Table 2.
The two models will allow us to compare the potential influences of additional three other NPIs on the effect of an individual NPI. Furthermore, mutually adjusted for the other three types of NPIs did not materially affect the conclusion.
In conclusion, we found that any type of NPI, namely mandatory face mask in public, isolation or quarantine, social distancing and traffic restriction, may reduce the spread of COVID-19. Social distancing seems more effective than the other three types of NPIs. The simultaneous implementation of two or more types of NPIs may be more effective for containing the spread of COVID-19.
More information: Rachel E. Baker et al, The impact of COVID-19 nonpharmaceutical interventions on the future dynamics of endemic infections, Proceedings of the National Academy of Sciences (2020). DOI: 10.1073/pnas.2013182117
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