Background
Coronavirus (SARS-COV-2) is now a global concern that speared out to 213 countries or territories as of September 15, 2020. More than 29.5 million population have been infected so far worldwide, of which more than 933,720 are died [1]. Consequently, the World Health Organization (WHO) has declared it as pandemic and suggested countries to take aggressive measures to reduce new infections [2]. Given no treatments or vaccines available for this virus, countries are now imposing numerous non-medical measures to reduce further infections, which include restricting people's movements, banned international and local travels, quarantine, and isolation [3]. However, the new infections are rising exponentially, in all ages and sexes, irrespective of the countries [4, 5]. Reducing new infections, therefore, needs further comprehensive preventive measures.
Knowing the accurate reproductive number of coronavirus, defined as the capability of transmission per primary infected person to the secondarily infected persons, is significant for various reasons, including to assess epidemic transmissibility and to predict the future trend of spreading [6]. These are important to reduce new infections through designing effective control measures such as social distancing [7] and to know the expected duration of keeping control measures [5]. Moreover, it also helps to develop an effective epidemiological mathematical model considering possible transmission ways, such as, droplets and direct contacts with coronavirus infected patients (COVID-19), which are important to know the risk population and the appropriate epidemiologic parameters [8, 9].
There are various researches in the country level that have been reported the reproductive number of coronavirus. However, they were not consistent in terms of their measurement procedures and methods used, therefore, the estimated reproductive number was quite different [8, 10]. Other reported sources of variations of the reported reproductive number were the country for which the reproductive number was estimated and its stages of infection and preventive measures applied [11]. Another important source of variation of the estimated reproductive number was the type of reproductive numbers considered [8]. Of the three reproductive numbers estimated, namely the basic reproductive number (R0), net reproductive number (Re), and time dependent reproductive number (Rt), are applicable for different purposes. For instance, the basic reproductive number is used when an infected person can mix randomly to non-infected persons (i.e., no control intervention was applied), whereas, the net and time-dependent reproductive number are used when control interventions were applied.
To settle these disagreements on the reported reproductive number and know the current situation of infection, a summary estimate of the reproductive number is important. However, of the three studies that have been provided summary reproductive number so far were limited in several areas and did little to settle these disagreements [12–14]. For instance, they reported a summary estimate of the basic reproductive number without considering the net reproductive number and the time-dependent reproductive number. However, it is around 10 months that have already been gone since the first infection of the coronavirus in December 2019 and all countries have been imposed several prevention measures. Therefore, the estimation of the basic reproductive number was available only in a few studies of which these summary estimates were based. Moreover, these studies were also failed to address the heterogeneity of their estimated reproductive number though it was found higher [12–14].
Considering the higher variability of the reported reproductive number and lack of relevant research, in this study, an attempt has been made to provide a summary reproductive number of coronavirus. The sources of variation of the reported reproductive number were also addressed. Findings will help policymakers to know about the possible increase of coronavirus infected patients and take policies and programs accordingly.
Discussion
This review aimed to provide the summary reproductive number of the coronavirus based on the global level evidence. A total of 42 studies selected for this study of which 29 studies were included in the meta-analysis. Majority of the included studies were conducted in China. The estimated summary reproductive number was 2.87. We found evidence of higher heterogeneity of the reported reproductive number across different studies. The sources of heterogeneity were the country for which the reproductive number was estimated, models and methods that were used to estimate the reproductive number, and the total number of case that was used to estimate the reproductive number.
The average estimated reproductive number was 2.87; which is higher than the WHO’s estimate of 1.4 to 2.5. However, this estimate is lower than the previous summarized reproductive number of coronavirus, 3.38 estimated by Alimohamadi and Colleagues based on the 23 studies [12], 3.15 reported estimated by He and colleagues [14] based on the 7 studies, and 3.28 estimated by Liu and colleagues based on the included 12 studies [13]. Numerous measures to reduce new infections of coronavirus such as social distancing, and controlling international travels are associated with such reduction [54, 55]. However, our estimated reproductive number is still very high that could have the potential to an exponential increase in new infections. Moreover, the estimated number is still very higher than previous rounds of coronavirus like infectious diseases, such as severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS) if we considered the period between the when was estimation done and infections were initially detected. For instance, the reproductive numbers of SARS and MERS were reduced to 0.95 (95% CI, 0.61–1,23) and 0.91 (95% CI, 0.36–1.44), respectively, after 3rd generation of the infection [56]. There are numerous reasons for such a higher reproductive number. First, biological facts of the infection rate and duration of contagion are important to explain such higher reproductive number instead of strict control measures that placed to reduce new infections [57]. For instance, a person could be infected in numerous ways, such as gets physically contacted with the infected person or through environmental transmission by respiratory droplets [58]. Moreover, coronavirus infected patients may not show symptomatic characteristics upto two weeks of infection. This pre-symptomatic stage is another vital source to increase new infections exponentially as in this period an infected person is usually confounded in the community with other people. This risk is further increased significantly for the country where population density is high [59].
This study also found evidence of the very high (99.5%) heterogeneity of the estimated reproductive number. Along with the factors described above, the study’s characteristics were found as the important sources for such higher heterogeneity. For instance, the reproductive number found higher for the countries where no restriction was applied, or restriction was applied in delayed. The forms of restrictions were to control people’s movement, to monitor personal hygiene, and to impose to wearing a mask [60, 61]. These implications act to control virus transmission from an infected to the susceptible and reduce the new infections. These also affect the average transmissibility of coronavirus within the specific population and settings [62, 63].
Estimation models, assumptions applied, and estimation processes were empirical sources of variability of the estimated reproductive number of coronavirus [64]. For instance, studies included in this analysis were followed assumption of generation time (which is followed by the gamma distribution) or serial interval (which is followed by the poison distribution) which is an important source of heterogeneity [65–67]. The reason of such difference is the underlying concept: generation time refers to the average time between transmission the virus from an infected person to the non-infected person whereas serial interval refers duration between onset of symptoms in an index case to the transmission in a secondary case [65, 66, 68]. Moreover, the estimated reproductive number generated by mathematical models is dependent on numerous decisions made by the researcher such as homogeneity or heterogeneity of the population considered; use a deterministic or stochastic approach and which distributions to be used to describe the probable values of parameters [57].
We found the type of reproductive number considered was another important source of heterogeneity of the estimated reproductive number. For instance, this study found the summary of the basic reproductive number was 1.95, around half of the summary of the estimated time-dependent reproductive number (4.42). Three previous meta-analyses found the summary estimate of the basic reproductive number ranged from 3.15 and 3.38 [12–14]. The sources of such heterogeneity are the underlying assumptions and the period between the initial infection and date of estimation [65, 69].
This study was first of its kind that provides an estimation of reproductive numbers based on the global literature. Moreover, we have considered the heterogeneity of the reproductive numbers estimated worldwide and explored the sources of heterogeneity across the characteristics of the selected papers. However, many other factors may explain the sources of heterogeneity of the reported reproductive number of coronavirus worldwide which was not explored in this study because of the lack of data.
10.1371/journal.pone.0242128.r001
Decision Letter 0
Flacco
Maria Elena
Academic Editor
2020
Maria Elena Flacco
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version
0
13 Sep 2020
PONE-D-20-16375
Reproductive number of COVID-19: A systematic review and meta-analysis based on global level evidence
PLOS ONE
Dear Dr. Khan,
Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.
In addition to the comments raised by the Reviewer, there are other issues that need to be addressed. Specifically:
1. Given that the authors are approaching a meta-analysis on such a specific topic, they should have made it clear that COVID-19 is not the virus (which is, indeed, called SARS-CoV-2). COVID-19 stands for Coronavirus disease-19, and is the disease caused by the virus, so the basic reproduction number cannot be referred to the disease, but to the etiological agent. Please do correct everywhere in the title, abstract, manuscript, tables and figures, where appropriate. No additional revision process can be carried on in the absence of this basic requirement.
2. The data search dates back to April 10, 2020. Given the rapidly evolving epidemiologcal scenario, the search needs to be updated to eventually include any new published study.
3. "Data extraction and Analysis" paragraph, page 8, lines 4-5: "For the studies where more than one reproductive number reported based on different assumptions, we calculated the average reproductive number. This calculated average reproductive number was then used to give summary estimate". This approach is not entirely correct. When multiple estimates are available for the same study, a pooled estimate should be computed from the available data using a fixed-effect meta-analysis. Then the resulting estimate should be included in the overall meta-analysis (see as an example Flacco et al Heart 2020; heartjnl-2020-317336).
4. Table 2: some results from a meta-regression are listed, but they are not commented in the results, nor reported in the methodology: please do clarify.
5. Page 7, last line: "Meta-analysis [WAS] then used to give an average estimate of the reproductive number". The estimate resulting from a meta-analytical approach is not simply an average, and should not be defined as such. It is a pooled, or summary estimate. Please do correct everywhere in the text where appropriate.
6. At least two previous meta-analyses were published on the same topic (He W et al. J Med Virol. 2020 May 29:10.1002/jmv.26041. doi: 10.1002/jmv.26041; Alimohamadi Y et al. J Prev Med Public Health. 2020 May;53(3):151-157. doi: 10.3961/jpmph.20.076). Please discuss your results also in light of these previous findings.
7. Minor issues:
- The length of the introduction could be easily reduced, as many of the reported information on the hystory of the pandemic and on the main characteristic of the SARS-CoV-2 virus are already well known, and could be reduced to one or two short paragraphs. Please go straight to the point.
- The manuscript needs a careful language editing, as there are some errors and misspellings (see as an example: "Meta-analysis WAS then used to give an average estimate of the reproductive number.", or "the estimated reproductive number was around double (..) in outside of China than China").
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Reviewer #1: Yes
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Reviewer #1: Yes
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Reviewer #1: Yes
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Reviewer #1: Abstract:
Aim and study methodology is fairly stated but need to touch on some special feature on the topic to provoke read full paper.
Introduction:
Introduction could have been more effective. Context of the study is moderately stated but lacks enough logical progression. Importance of this study should benefit the readers and provide a rough solution which will be convinced in discussion section.
Please refer to the previous meta-analyzes(for example: Estimate of the Basic Reproduction Number for COVID-19: A Systematic Review and Meta-analysis. Alimohamadi, Yousef et al. J Prev Med Public Health 2020; 53(3): 151-157. DOI: https://doi.org/10.3961/jpmph.20.076) and mention the relative advantages of your work over previous studies.
Figure 1 needs to be self explanatory with stand alone graphics. a and b are not shown in the fig.
Methodology:
Selection, presentation and sampling of various studies were fairly explained. As you mentioned in the introduction section there are at least 3 types of R, but according to the search strategy, it is not clear which type of R has been studied. Has subgroup analysis been performed for different types of R? If yes, why aren't the results presented?
If possible, some insights from the authors about possible reasons for those larger outliers (around 6), or any particular characteristics of those studies (e.g. small sample, earlier stage, or particular region?)
Results:
Figures and tables needs to be self explanatory with stand alone graphics.
Please provide the results of the quality assessment of each study in the table 1.
Please provide the detailed results of the funnel plot , Egger’s test and Trim-and Fill procedure.
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10.1371/journal.pone.0242128.r003
Decision Letter 1
Flacco
Maria Elena
Academic Editor
2020
Maria Elena Flacco
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version
1
28 Oct 2020
Reproductive number of coronavirus: A systematic review and meta-analysis based on global level evidence
PONE-D-20-16375R1
Dear Dr. Khan,
We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.
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Maria Elena Flacco, M.D.
Academic Editor
PLOS ONE
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Reviewer #1: All comments have been addressed
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Reviewer #1: Yes
**********
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Reviewer #1: I Don't Know
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Reviewer #1: No
**********
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Reviewer #1: Yes
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