1 Introduction

COVID-19 is caused by novel strain of virus SARS-CoV-2 emerged from China and now declared as pandemic due to its presence across the continents in more than 213 countries. Based on genetic analysis SARS-CoV-2 is grouped in a family Coronaviridae, genus Betacoronavirus and subgenus Sarbecovirus (Benvenuto et al. 2020; Lau et al. 2020; Lu et al. 2020). Coronaviruses are known to infect series of animals, birds, rodents, reptiles and humans (Ji et al. 2020). Similarly, SARS-CoV-2 is also zoonotic in nature by showing animal to human transmission. SARS-CoV-2 is reported to share 96% nucleotide identity with horseshoe bat (Rhinolophus affinis), suggesting it as a natural host (Andersen et al. 2020; Paraskevis et al. 2020). It is further assumed that SARS-CoV-2 moved from bats to an intermediate host Malayan pangolin (Manis javanica) sharing 91% nucleotide identity and then to humans (Lam et al. 2020; Zhang et al. 2020a, b, c). The capability of coronaviruses for host switching demonstrates strong adaptive capacity, suggesting that there can be other possible intermediate hosts (Smith and Denison 2012). More elaborate research and studies are required to examine wide variety of animals as an intermediate host.

SARS-CoV-2 is deadly due to its high transmission and fatality rates (Carleton and Meng 2020). At present average fatality rate from COVID-19 is reported to be 3.4% (Rajgor et al. 2020). Structural modelling depicts that SARS-CoV-2 readily binds with human cell receptor present in lungs, intestine, kidney, and heart (Clerkin et al. 2020). This cell receptor serves as the entry point for some coronaviruses present in a diverse group of animals (Zhou et al. 2020) and regulates cross-species transmission (Wan et al. 2020). SARS-CoV-2 enters the body primarily through nose, eyes and mouth. From the time of initial exposure, it takes two weeks (14 days) for a person to develop symptoms called as incubation period, but, in some cases, it may be as long as 24 days (Abduljalil and Abduljalil 2020). First it infects upper respiratory tract causing dry cough and fever (Jiang et al. 2020).

Researchers around the world were speculating seasonal transmission, where COVID-19 will exist in winters, and as soon as temperature will rise, there are chances of less transmission. Therefore, spread of cases is dependent on temperature and humidity (Bherwani et al. 2020a). It was estimated that 1 °C rise in temperature reduces transmission by 13% (Carleton and Meng 2020). Doubling time correlates positively with temperature and inversely with humidity (Oliveiros et al. 2020). But increase of temperature would alone not necessarily lead to decline in cases, but it should also be coupled with other mitigation measures. It was believed that develo** countries with lack of medical facilities will face more mortality than developed countries. But in reality, given the present scenario developed countries had more cases and mortality as opposed to develo** countries. It is believed that higher mortality in developed countries is due to the presence of elder populations, whereas develo** countries have a younger population (Walker et al. 2020). It was reported that children are least affected, whereas the elderly are experiencing highest rate of deaths (Guo et al. 2020). Children tend to make more social contacts than adults and therefore contribute more to transmission than adults (Davies et al. 2020). It was also evident that more symptoms were visible with age above 60 years and there were no cases in children below 15 years of age (Li et al. 2020a, b; Zhang et al. 2020a, b, c). Average recovery time for COVID-19 is estimated to be 22 days with 19 days for young people and 22 days for older groups (Bi et al. 2020). It was reported that mortality rate in Italy (5.4%) was higher than China (2.3%) due to the presence of elderly population (Abduljalil and Abduljalil 2020). Cases were more in males and between the ages of 20–69 years (Bi et al. 2020). Recent study in China surprisingly reported SARS-CoV-2 in the semen of male patients raising new debate on sexual transmission of the disease (Li et al. 2020a, b).

With every passing time new development related to COVID-19 is stated with respect to transmission mode and transmission rate. Other possibilities of transmission from human to pet transmission, waterborne transmission, transmission through air etc. (Gautam and Hens 2020; Gautam 2020a) are speculated but remain uncertain. It is an initial phase of this pandemic and is believed that COVID-19 will take longer time to get completely eradicated. However, control measures can slow down the speed as well as mortality rate.

3 Mitigation methods adopted to control COVID-19

Immediate and strategic response to mitigation plays an important role in influencing the trajectory of this pandemics across the world. In case of Wuhan, China, there was decline in transmission when control measures were introduced (Kucharski et al. 2020). It was estimated that the absence of mitigation measure would lead to 7 billion infections and 4 billion deaths (Walker et al. 2020). Various measures are undertaken to prevent infection such as maintaining hygiene, using facemasks, isolation/quarantine, social distancing, in extreme cases lockdown in hot spot areas.

Proper hygiene practices were encouraged such as covering the nose/mouth with tissue or elbow while coughing/sneezing and avoid touching surfaces (Bruin et al. 2020). The use of hand sanitizer or washing hand with soap for 20 secs after sneezing or touching contaminated surfaces was essential. Surfaces were decontaminated with many solutions such as ethanol, isopropyl alcohol, sodium hypochlorite bleach, hydrogen peroxide. Face masks became an essential component but was recommended only when having symptoms or treating patients. Its importance was apparent from the fact that one patient without facemask transmitted virus to five other people while travelling in a vehicle in China (Liu and Zhang 2020; Liu et al. 2020a, b). In develo** countries, due to lack of sufficient medical mask, people started use of local cloth mask. Cotton mask could be a potential substitute for medical mask as there is no significant difference for reducing droplet transmission. Cotton mask is washable and re-usable also (Ho et al. 2020).

Health, transportation, safety, security and infrastructure workers were at highest risk of getting infected and therefore were provided first priority for personal protective equipment (PPE). Source control by masking of patients and visitors by using N95 or higher-level respirators, using telemedicine, designating separate locations/rooms for care also helped in reducing risk of SARS-CoV-2 transmission in health workers (Heinzerling et al. 2020). The virus may be resuspended from the contaminated PPE surface to the air; therefore, sanitization before they are taken off was carried out to reduce the infection risk for health and other workers (Gautam 2020b; Liu et al. 2020a, b). At present, there is no definite vaccine present to treat COVID-19, but many medicines such as remdesivir, chloroquine, lopinavir and ritonavir were successfully used as an alternative (Gabriella et al. 2020; Guo et al. 2020).

Social/physical distancing was encouraged by avoiding groups and kee** safe distance of 1-2 m (Bruin et al. 2020). Social distancing when coupled with isolation/restrictions likely to control the disease within 13–14 weeks and reduced peak incidence by 40–60% was estimated (Chang et al. 2020; Zhang et al. 2020a, b, c). Isolation practices can be effective for preventing secondary transmission of viruses (Basile et al. 2020). About 80% of individuals needed to be traced and isolated to attain 90% control over outbreak (Hellewell et al. 2020). In hot spot areas with highest number of cases lockdown was imposed in many countries. It included complete closure of public transport, public places, educational institution, hotels, offices, factories, etc. Lockdown resulted into decline of transmission of disease to half (Kucharski et al. 2020). China initiated lockdown to control the disease followed by Italy, France, Spain, Philippines, India and other countries.

Technology intervention such as the use of digital technologies for screening infected individuals was vital in controlling transmission and slowing pace of the disease in Taiwan, Singapore, Hong Kong and South Korea. Countries around the world launched websites/apps to combat misinformation regarding disease, medication and encourage awareness. Some of the examples are Self Diagnosis App (South Korea), EuroMOMO (Europe), Aarogya Setu (India), Mask app (Iran), Trace Covid (UAE), Crush Covid app (USA), Corona-Warn app (Germany), StopCovid app (France), Covid-Safe app (Australia), Tracetogether app (Singapore), Immuni app (Italy) COVID-19 GIS Dashboard by John Hopkins CSSE (USA), Worldometer coronavirus tracker, WHO COVID-19 Dashboard, COVID-19 India tracker, etc. This tracker app shows total number of cases in surrounding area and alerts about hot spot/containment zone. Also, e-pass is provided in case of the absence of corona symptoms.

4 Bayesian Probability Modelling for COVID-19 Transmission

It is recognized that the SARS-CoV-2 is highly contagious and till the medications are being explored, and social/physical distancing along with hygiene is the only saviours (Bherwani et al. 2020a). CPA is performed in Table 1 in order to understand the most impacting week for the countries in terms of either increase or stagnation in number of COVID-19 cases. The countries were chosen based on better availability of data. Python-based PyMC3 is used for CPA.

The above probabilistic programming of Python is used to fit Bayesian models using varied numerical methods (Salvatier et al. 2016). Here this model is used as per the concept that more than frequency of any parameter, the reasonability and expectation of an event are more important. In such circumstances Bayesian probability is usually used. Proportional logic is used to derive the reasoning of interaction. The assessment could have been carried using other methods of probability; however, the above method suits the best under the given circumstances. Similar approaches have been used in past as well (Aminikhanghahi and Cook 2017; Bherwani et al. 2020c). The model is built for series of data (Table 1), and CPA is determined for each country, viz. India (A), USA(B), France(C), Italy(D), Japan(E), Iran(F), Spain(G), and China(H). The results of CPA are shown in Fig. 2A–H and summarized in Table 2. The raw images of Fig. 1 are given in Appendix. The orange line indicates the point where drastic change has occurred in the number of COVID-19 cases in each of the respective countries, referred to as change point (CP). It can be seen that each country had shown a different response to the pandemic except China is showing a band rather than a point of change, as the cases suddenly increased and stabilized in the country.

Fig. 2
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CPA results for each selected country

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Table 2 Significance of change point with respect to lockdown
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CPA is further analysed in reference to the first cases which are observed in respective countries and the day on which lockdown is initiated as shown in Table 2. This is important in order to understand if the lockdown is initiated before or after change point. The difference gives a significant information. Table 2 indicates the list of countries which were able to act fast and start physical distancing measures before the catastrophe (point of change) occurred in terms of exponential rise of COVID-19 cases. Countries including India, Italy, Japan, Spain and China acted relatively fast. While Italy and Spain have suffered with many cases and fatalities, India, Japan and China have been able to contain the spread and flatten the curve given their steady rise in cases. USA, which acted very late, has borne the brunt of the virus which is visible in their exponential rise and sheer magnitude of number of cases in such a short time. While the CPA indicates the importance of social distancing, it is worthwhile to explore its linkage with COVID-19 by adding one more parameter of population, i.e. normalized population and population density. Table 3 gives a comparative analysis of the same.

Table 3 CPA results in relation to cases and population
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Table 3 is arranged in decreasing order of cases per unit population density (CPD), which is an indicator of penetration of COVID-19 into the country. It can be clearly seen that the countries which acted late have more cases per unit population density. USA and Iran with the slowest response have the maximum CPD. Iran is standing below USA, probably due to lower absolute population. Furthermore, Spain had an earlier response than Italy and was able to control CPD better despite having higher population and population density. India and Japan had an ascendency in terms of delta (d), indicating the early action, and are the lowest in terms of CPD. India is best among the lot probably because of executing one of the most stringent lockdowns ever. China is an exception due to facts stated above. The results are represented in Fig. 3 with Log10 values of CPD considered for normalization of scale. It indicates that with increase in the values of delta, there is steady drop in Log10 CPD values. Further analysis is carried out for countries having positive delta (except China) in terms of their linear correlation with population parameters. The results are shown in the form of lower triangular matrix in Table 4.

Fig. 3
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Importance of early action in control of COVID-19 spread

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Table 4 Correlation matrix for delta and population parameters
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From Table 4, it can be inferred that D is in strong inverse correlation with number of cases, CPP and CPD with factors of − 0.86, − 0.97 and − 0.97, respectively. This indicates that more the value of delta, lesser are the CPP, CPD and C values which establishes the hypothesis that lockdown and physical distancing are playing a major role in reducing the intensity and magnitude of cases of COVID-19. Also, population density is an important factor when it comes to the spread of the virus which reconfirms the causation that the virus is highly contagious in nature and physical distancing is one of the most efficient ways to control its spread. While there is sufficient evidence that the extremely contagious nature of this virus and population density are playing an important role in spread of COVID-19, it is important to note that as the world moves through this pandemic, the models will have to be adapted to improve the predictions and the same is true for the above modelling exercise as well.

5 Discussion and Conclusion

COVID-19 has proven to be once in lifetime pandemic that a generation will ever experience. It is a silent war that a human is fighting with an organism of nanosize. Developed countries claiming their efficiency in health and other facilities have given up to the atrocities created by this virus. The virus which is named as SARS-CoV-2 has its presence in every country and continent across the world. It is transmitted from Horseshoe bat (natural host) through Malayan pangolin (intermediate host) finally to the humans. First detected in China and then spread rapidly in other countries initially from people having travel history to infected countries. Airborne, droplet and fomite transmission are held responsible for local transmission. Population were encouraged to use hand sanitizers, soap, facemask/face covering, etc., to prevent from COVID-19. It is believed that increase in temperature in coming months will also help to slow the pace of COVID-19 and death rates will decrease. It is reported that COVID-19 mostly effects and elderly population (Fig. 4).

Fig. 4
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Transmission of COVID-19 symptom, mitigation measures adopted and effect on population

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The paper explores the efficacy of the lockdowns and social distancing polices followed by eight countries suffering from COVID-19 pandemic. While lockdown has a strong effect on the economy and many people will lose their jobs, creating financial insecurity, lockdown seems to be an efficient way of controlling the spread (Bherwani et al. 2020b). CPA showed that social distancing and lockdown have helped many countries to bring down their number. The countries which were able to act before the curve became exponential and implemented their social/physical distancing measures have been able to contain their numbers. A strong inverse correlation between the time of action, represented by delta, and the number of cases (Pearson’s r = − 0.86), cases per unit population and population density (Pearson’s r = − 0.97), are representative of depth of penetration of the disease. It is evidently seen the countries like India and Japan are among those who introduced lockdowns and distancing measures way early during the spread have much less cases, rate of increase of cases, while on the other hand, countries like USA, Italy, Spain and France have been suffering due to the late action on the above mitigation measures. The outcome of the research not only helps the countries which are still struggling with the virus, especially develo** countries, but also it is helpful for the expected second wave of the virus. The analysis can be used to develop strategies related to mitigation and control of the spread of virus as it indicates the population density is one of the major factors driving the spread. Future research on similar lines can be carried out to understand the effect of life style and pre-existing conditions similar to population density using the above given novel approach.