COVID

A global analysis of the impact of non-pharmaceutical interventions (NPIs) on the dynamics of the spread of the COVID-19 indicates that these can be classified using the stringency index proposed by the Oxford COVID-19 Government Response Tracker (OxCGRT) team. The world average for the coefficient that linearises the level of transmission with respect to the OxCGRT stringency index is s = 0.01{+/-}0.0017 (95% C.I.). The corresponding South African coefficient is s = 0.0078 {+/-} 0.00036 (95% C.I.), compatible with the world average. Here, we implement the stringency index for the recently announced 5-tier regulatory alert system. Predictions are made for the spread of the virus for each alert level. Assuming constant rates of recovery and mortality, it is essential to increase s. For the system to remain sub-critical, the rate with which s increases should outpace that of the decrease of the stringency index. Monitoring of s becomes essential to controlling the post-lockdown phase. Data from the Gauteng province obtained in May 2020 has been used to re-calibrate the model, where s was found increase by 20% with respect to the period before lockdown. Predictions for the province are made in this light.

Following the widespread vaccination program for COVID-19 carried out in Israel, a survey was conducted to preliminarily assess behavior changes in the vaccinated population, prior to the expected upcoming policy change as to mask wearing and social distancing regulation in Israel. 200 people answered at least one question pertaining to preventive behaviour. Among the respondents, 21.1% reported a decrease in mask wearing compared to 47.3% who reported a decrease in social distancing. There was no difference in these measures between the sexes. However, people under the age of 50 were more likely to decrease mask wearing (28.1%) and decrease social distancing (56.1%), as compared with people over the age of 50 (17.2% and 41.8%, respectively). Among health care workers, there was a minimal decrease in mask wearing (1/23 people) compared to a more widespread decrease in social distancing (10/23). These data suggest that preventive attitudes change following COVID-19 vaccination, with less adherence to social distancing as compared to mask wearing, and should be taken into account when planning public policy in the future.

In the second year of the COVID-19 epidemic in the Southeast Asia (SE) regions, there is a plan to reopen the school, including the campus. Among students in Indonesia, college students have a population of almost 8.3 million. Considering the massive numbers of college students, school reopening should be supported by adequate COVID-19 vaccination. As a result, the first dose of the inactivated virus COVID-19 vaccine has been administered, including to college students aged over 18 years old. While COVID-19 vaccination is widely available, there is still a scarcity of information on post-vaccination symptoms. As reported from other locations, post vaccination has been reported. Then, this study aims to assess the common symptoms of COVID-19 1st dose vaccinations among the following groups: gender (male and female college students), age, body weight, and height. The observed symptoms include sore arms, fatigue, headache, fever with a body temperature above 38 {degrees}C, nausea, shivering, and muscle joint pain. Participants in this study were students at the university. They were considered eligible for this study if they were currently enrolled at university, were at least 19 years of age, and provided informed consent. The data was recorded using a standardized online questionnaire. The answers were collected in an online database. At the beginning of the questionnaire, subjects or students were informed that data would be collected anonymously. Based on the results, the symptoms were different between female and male students. In fact, female students have experienced more symptoms than male students. While male students only suffered sore arms (68%) followed by headache symptoms (32%). Similar to male students, sore arms are the most common symptom observed among female students. Among female students, from the most to the least common symptoms observed from 20 years of age in this study are sore arms at site reaction > headache > fatigue > fever > muscle joint pain > shivering > nausea. A higher risk of presenting fatigue and headache symptoms was found in those with a non-overweight status with weight ranges of 50-60 kg.

Prior to lockdown the spread of COVID-19 in UK is found to be exponential, with an exponent =0.207. In case of COVID-19 this spreading behaviour is quantitatively better described with a mobility-driven SIR-SEIR model [2] rather than the homogenous mixing models Lockdown has dramatically slowed down the spread of COVID-19 in UK, and even more significantly, has changed the growth in the total number of infected from exponential to quadratic. This significant change is due to a transition from a mobility-driven epidemic spreading to a spatial epidemic which is dominated by slow growth of spatially isolated clusters of infected population. Our results strongly indicate that, to avoid a return to exponential growth of COVID-19 (also known as "second wave"), mobility restrictions should not be prematurely lifted. Instead mobility should be kept restricted while new measures, such as wearing of masks and contact tracing, get implemented in order to prevent health services becoming overwhelmed due to a resurgence of exponential growth.

BackgroundFull immunization with two doses of Covid vaccine has been found to be a critical factor in preventing morbidity and mortality from the Covid-19 infection. However, due to the shortage of vaccines, a significant portion of the population is not getting vaccination in many countries. Also, the distribution of vaccine doses between prospective first dose recipient and second dose recipient is not uniformly planned, as seen in Indias various states and union territories. It is recommended to give second vaccine doses within 4-8 weeks to first dose recipients for both the approved vaccines in India; hence the judicious distribution between non-immunized and partly immunized populations is essential. Managing the Covid-19 vaccination drive in an area with a large number of single-dose recipients compared to a smaller number of fully immunized people can become a huge administrative challenge. Therefore, this study was conducted to assess the number of people covered under the Covid vaccination drive in India and analyze the state-wise distribution of vaccines among the non-immunized and partly immunized population. MethodsThe Covid 19 vaccination data till 7th may, 2021 was taken from the website of the Ministry of Health and Family Welfare, Govt of India. From the data available of the number of doses injected, other figures like the total number of people vaccinated, people with two doses of vaccine or full immunization (FI), and those with a single dose of vaccine or partial immunization (PI) were found. The percentage of the fully immunized and partly immunized population was also found. A ratio between fully immunized and partly immunized individuals (FI: PI) was proposed as a guide to monitor the progress of the vaccination and future dose distribution of two-dose Covid-19 vaccines among partly immunized (PI) and non-immunized (NI) population. ResultsIn India, till 7 May 2021, 16,49,73,058 doses of Covid-19 vaccines have been injected. A total of 13,20,87,824 people received these vaccine doses, with 9,92,02,590 people getting a single dose or were partly immunized (PI), and 3,28,85,234 got two doses each or were fully immunized (FI). Among the states, Tripura and Andhra Pradesh had the highest FI: PI (Fully Immunized: Partly Immunized) ratio of 0.86 and 0.52, followed by Tamil Nadu, Arunachal Pradesh, and West Bengal with figures of 0.48. 0.47 and 0.47, respectively. Telangana and Punjab had the lowest FI: PI ratio among the states at 0.2 each, with Chhattisgarh, Madhya Pradesh, and Haryana following at 0.21. 0.23 and 0.23, respectively. These values are much lower than the national average of 0.33 in India. ConclusionThe FI: PI ratio could help governments decide how to use scarce vaccine resources among first-time and second-time recipients. This simple mathematical tool could ensure full immunization status to maximum people within the recommended 4-8 week time window after the first dose to avoid a large population group with partly immunized status.

IntroductionOn August 13, 2021, India completed 30 weeks of vaccination against COVID-19 for its eligible citizens. While the vaccination has made progress, there has been no study analyzing the federal/union vaccine policy and its effect on vaccination coverage across Indian states. In this context, this study analyses the federal vaccination policy and its effect on interstate variation in vaccine coverage and the correlation of state economy with vaccination coverage. MethodsThe study analyses vaccine policy documents, secondary data on vaccination coverage and state gross domestic product (GDP) available in public domain. ANOVA test has been used to assess the effect of vaccine policy on interstate vaccine coverage and correlation-regression analysis has been conducted to assess the type and strength of association between gross state domestic product and vaccination coverage. ResultsInterstate variation in vaccination coverage in the first 15 weeks was the least (F=3.5), when vaccine procurement and supply was entirely provided by the union/federal government and vaccination was limited to priority groups. However, with the extension of vaccine policy to other groups and reduction in federal government involvement in vaccine procurement, the interstate variation in vaccination coverage increased significantly (F=10.74) by the end of 30 weeks. The highest interstate variation was observed in the period between 23-30 weeks (F=25.31). State GDP was positively and strongly correlated with state vaccination coverage with a high coefficient of correlation (R=0.94) and high coefficient of determination (R2= 0.88). ConclusionsThe study finds that federal procurement and supply of vaccination among prioritized groups has been the best strategy till date to address the inequity in vaccination coverage across the states of India.

It is a painful job to predict the death of people. But sometimes it is important to predict the future and concern the government. A furious future is waiting for Bangladesh. ObjectiveObjective of the study is to assume the number of positive case and death till 30th December, 2020 in Bangladesh. Study designThis study was designed with systematic review and data analysis. MethodThe study was completed by analyzing data available on website. First COVID 19 case in Bangladesh was identified on 8th March. Analyzing the data increasing rate/common ratio of infection and death has been identified. Then this common ratio has been used in the formula of multiplication series (at decreasing rate). Data of China, Iran, Italy and the USA was also analyzed to assume how the death and case number increased. Social issues of Bangladesh were also analyzed. Considering all these the assumption was made. ResultIt has been assumed that by the 43rd week (on 30th December, 2020) of first identification the total case can be 15640747 and total death can be 638769 by 30 December, 2020. As this is an assumption this can be true, partially true or false. But the base of assumption is strong enough so the possibility of being true or nearly true is higher. Policy SuggestionGovernment should choose properly one between two options. Either government should declare curfew or let people lead normal life for the purpose of herd immunity. A very weak lockdown for a long time doesnt make any sense.

BackgroundBreakthrough events are not rare after emerging of Delta variant. On the other hand, long COVID is an unsolved issue where sufferers suffer a lot. Some study has shown that COVID-19 vaccine has improved some clinical and libratory parameters in long COVID. But what will be the possible measures against long COVID after the breakthrough event is still a burning question. MethodWe have observed the third dose by BNT162b2 in a small group(n=20) who were diagnosed as long COVID after breakthrough infections, in Sheikh Hasina National Institute of Burn & Plastic Surgery Institute, Dhaka, Bangladesh. CRP(C-reactive protein) and Anti S1 RBD IgG responses were measured. ResultAll 20 participants in the study received both dosage of "ChAdOx1-nCoV-19" in between February 2021 to April 2021 and had breakthrough infection in the same or following month which led to long COVID syndrome. They all received a third dose of "BNT162b2". A before and after 3rd dose (14 days after) CRP from participants serum was measured. A Wilcoxon matched paired signed rank test revealed significant (P value <0.05) reduction of inflammatory marker (CRP) after receiving the 3rd vaccine dose. Pre and post 3rd dose quantitative anti S1-RBD IgG response was measured and compared that revealed significant boosting effect that clearly correlates with the CRP response. ConclusionCoverage of vaccines all over the world is still not expected level to control this pandemic. WHO has not recommended the use of a third/booster dose of COVID vaccines. Though our results show some sort of hope for the long COVID in breakthrough events after getting the third dose more study is needed to conclude this issue.

Humanity has experienced outbreaks for millennia, from epidemics limited to pandemics that have claimed many victims and changed the course of civilizations. The advent of vaccines has eradicated some of the serious pathogens and reduced many others. However, pandemics are still part of our modern world, as we continue to have pandemics as devastating as HIV and as alarming as severe acute respiratory syndrome, Ebola and the Middle East respiratory syndrome. The Covid-19 epidemic with 0-exponential contamination curves reaching 3 million confirmed cases should not have come as a surprise, nor should it have been the last pandemic in the world. In this article, we try to summarize the lost opportunities as well as the lessons learned, hoping that we can do better in the future. The objective of this study is to relate the situation of Covid-19 in African countries with those of the countries most affected by the pandemic. It also allows us to verify how, according to the observed situation, the African ecosystem seems to be much more resilient compared to that of other continents where the number of deaths is in the thousands. To verify this, the diagnosed morbidity and mortality reported for different states of the world are compared to the ages of life and the average annual temperature of these states. The results show that the less dramatic balance of the African continent compared to other continents is partly linked to the relatively high temperatures on the continent but also to the relatively young character of its population.

The global fight against the COVID-19 pandemic has underscored the critical importance of widespread vaccination to mitigate the impact of the virus on public health. The current study aimed to investigate which social influences might be most important for predicting attitudes towards COVID-19 vaccination and vaccine uptake among young students in the UK. We focused on the cultural evolution and social transmission aspects, i.e., parent-to-child versus peer-to-peer, of attitudes and vaccine uptake during the COVID-19 pandemic. A sample of 192 UK students (aged 18 to 35 years old) filled in an online survey including measures for attitudes towards COVID-19 vaccination and vaccine uptake and/or intention, age, and gender. Participants were also asked about their mothers, fathers, and best friends attitudes towards COVID-19 vaccination and vaccine uptake. Finally, they provided a subjective measure of the quality relationship with their parents. Overall, our results suggest that both parents and very close friends are important agents in understanding the students attitudes towards COVID-19 vaccination and vaccine uptake. More specifically, our findings suggest the mothers vaccine uptake as the most salient predictor of students attitudes towards COVID-19 vaccination and vaccine uptake, particularly when the students disclose having a positive relationship with their parents. In cases where students experience negative relationship with their parents, the best friends vaccine uptake may supersede the mothers influence. Despite these nuances, a general trend emerges from our data suggesting that vaccine uptake could be primarily guided by vertical transmission (i.e., parent to child). Our results have the potential to influence public health strategies, communication campaigns, and targeted interventions to enhance vaccination uptake. Identifying key social predictors can enable policymakers and health authorities to tailor vaccination promotion efforts towards mothers and peers vaccine uptake to increase overall positive attitudes and vaccine uptake among young people.

Kerala reported the first three cases of coronavirus in India in late January. Kerala, one of the Indias most densely populated states, which makes its success in fighting the Covid-19 all the more commendable. Moreover, an estimated 17% of its 35 million population employed or lives elsewhere, more than 1 million tourists visit each year, and hundreds of students study abroad, including in China. All of this mobility makes the state more vulnerable to contagious outbreaks. What is the strategy behind the success story? This paper compares the situation of COVID-19 pandemic in major states and Kerala by the different phase of lockdown, and also highlights Keralas fight against the pandemic. We used publicly available data from https://www.covid19india.org/ and Covid-19 Daily Bulletin (Jan 31-May 31), Directorate of Health Services, Kerala (https://dashboard.kerala.gov.in/). We calculate the phase-wise period prevalence rate (PPR) and the case fatality rate (CFR) of the last phase. Compared to other major states, Kerala showed better response in preventing pandemic. The equation for the Keralas success has been simple, prioritized testing, widespread contact tracing, and promoting social distance. They also imposed uncompromising controls, were supported by an excellent healthcare system, government accountability, transparency, public trust, civil rights and importantly the decentralized governance and strong grass-root level institutions. The "proactive" measures taken by Kerala such as early detection of cases and extensive social support measures can be a "model for India and the world".

To confront the global Covid-19 pandemic and reduce the spread of the virus, we need to better understand if face mask use is effective to contain the outbreak and investigate the potential drivers in favor of mask adoption. It is highly questionable since there is no consensus among the general public despite official recommendations. For the first time, we conduct a panel econometric exercise to assess the dynamic impact of face mask use on both infected cases and fatalities at a global scale. We reveal a negative impact of mask wearing on fatality rates and on the Covid-19 number of infected cases. The delay of action varies from around 7 days to 28 days concerning infected cases but is more longer concerning fatalities. We also document the increasing adoption of mask use over time. We find that population density and pollution levels are significant determinants of heterogeneity regarding mask adoption across countries, while altruism, trust in government and demographics are not. Surprisingly, government effectiveness and income level (GDP) have an unexpected influence. However, strict government policies against Covid-19 have the most significant effect on mask use. Therefore, the most effective way of increasing the level of mask wearing is to enforce strict laws on the wearing of masks.

The novel Coronavirus (2019-nCoV) was identified in Wuhan, Hubei Province, China, in December 2019 and has created a medical emergency worldwide. It has spread rapidly to multiple countries and has been declared a pandemic by the World Health Organization. In India, it is already reported more than 18 thousand cases and more than 600 deaths due to Coronavirus disease 2019 (COVID-19) till April 20, 2020. Previous studies on various viral infections like influenza have supported an epidemiological hypothesis that the cold and dry (low absolute humidity) environments favor the survival and spread of droplet-mediated viral diseases. These viral transmissions found attenuated in warm and humid (high absolute humidity) environments. However, the role of temperature, humidity, and absolute humidity in the transmission of COVID-19 has not yet been well established. Therefore the study to investigate the meteorological condition for incidence and spread of COVID-19 infection, to predict the epidemiology of the infectious disease, and to provide a scientific basis for prevention and control measures against the new disease is required for India. In this work, we analyze the local weather patterns of the Indian region affected by the COVID-19 virus for March and April months, 2020. We have investigated the effect of meteorological parameters like Temperature, relative humidity, and absolute humidity on the rate of spread of COVID-19 using daily confirm cases in India. We have used daily averaged meteorological data for the last three years (2017-2019) for March and April month and the same for the year 2020 for March 1 to April 15. We found a positive association (Pearsons r=0.56) between temperature and daily COVID-19 cases over India. We found a negative association of humidity (RH and AH) with daily COVID-19 Cases (Persons r=-0.62, -0.37). We have also investigated the role of aerosol in spreading the pandemic across India because its possible airborne nature. For this, we have investigated the association of aerosols (AOD) and other pollutions (NO2) with COVID-19 cases during the study period and also during the first lockdown period (25 March-15 April) in India. We found a negative association in March when there were few cases, but in April, it shows positive association when the number of cases is more (for AOD it was r=-0.41 and r=0.28 respectively). During the lockdown period, aerosols (AOD) and other pollutants (NO2; an indicator of PM2.5) reduced sharply with a percentage drop of about 36 and 37, respectively. This reduction may have reduced the risk for COVID-19 through air transmission due to the unavailability of aerosol particles as a base. HYSPLIT forward trajectory model also shows that surface aerosols may travel up to 4 km according to wind and direction within three h of its generation. If coronavirus becomes airborne as suggested by many studies, then it may have a higher risk of transmission by aerosols particles. So relaxing in the lockdown and environmental rules in terms of pollutant emissions from power plants, factories, and other facilities would be a wrong choice and could result in more COVID-19 incidences and deaths in India. Therefore the current study, although limited, suggests that it is doubtful that the spread of COVID-19 would slow down in India due to meteorological factors, like high temperature and high humidity. Because a large number of cases have already been reported in the range of high Tem, high Relative, and high absolute humidity regions of India. Thus our results in no way suggest that COVID-19 would not spread in warm, humid regions or during summer/monsoon. So effective public health interventions should be implemented across India to slow down the transmission of COVID-19. If COVID-19 is indeed sensitive to environmental factors, it could be tested in the coming summer-monsoon for India. So the only summer is not going to help India until monsoon is coming. Only government mitigations strategies would be helpful, whether its lockdown, aggressive and strategic testing, medical facilities, imposing social distancing, encouraging to use face mask or monitoring by a mobile application (Aarogya Setu). HighlightsO_LIFirst study on the effects of meteorological factors on COVID-19 cases in India. C_LIO_LIA positive association between daily new cases of COVID-19 with temperature. C_LIO_LIRH and AH are negatively associated with daily new cases of COVID-19. C_LIO_LIEarly lockdown in India slows down the spread of contagious disease COVID-19. C_LIO_LIMore than a 35% fall was found in AOD and NO2 values during the lockdown period. C_LI Graphical abstractCorrelation of daily confirmed cases of COVID-19 with the Temperature, Relative Humidity, and Absolute humidity from 20 March -15 April 2020 for the Indian region. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/20075499v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@da8163org.highwire.dtl.DTLVardef@164912corg.highwire.dtl.DTLVardef@1770f9aorg.highwire.dtl.DTLVardef@1a183b5_HPS_FORMAT_FIGEXP M_FIG C_FIG

Unexpected rapid infection involving SARS-CoV-2 variant Omicron known as the fifth wave of outbreak occurred since early January 2022 in Hong Kong. Almost 1.2 million citizens were infected in three months. Ventilation provisions in some gathering places with close contact such as restaurants were found to be lower than requirements, believed to be one of the main causes of transmission in these indoor spaces. At the end of the fifth outbreak in mid-May 2022, group infections were still found in several such gathering places including restaurants and pubs due to inadequate ventilation provisions. There are worries about triggering the sixth wave of outbreak. Key points related to ventilation requirements in such gathering places are discussed in this paper. Adequate ventilation of 6 air changes per hour minimum must be provided to avoid direct air transmission of virus. Indoor aerodynamics induced by ventilation system must be considered too. However, it is difficult to measure ventilation rate quickly and accurately. A control scheme on virus outbreaks is proposed on installing mechanical ventilation energy use meters and carbon dioxide sensors for checking ventilation provisions adequacy quickly.

There is some consensus in Europe and Asia about high testing rates being crucial to controlling COVID-19 pandemics. There are though misconceptions on what means an effective high testing rate. This paper demonstrates that the rate of tests per detected case (Tests/Case) is the critical variable, correlating negatively with the number of deaths. The higher the Tests/Case rate, the lower the death rate, as this predictor is causally related to contact tracing and isolation of the vectors of the disease. Doubling Tests/Case typically divides by about three the number of deaths. On the other hand, the per capita testing rate is a poor predictor for the performance of policies to fight the pandemics. The number of tests per 1,000 inhabitants (Tests/1,000) tends to correlate positively with the number of deaths. In some cases, high levels of Tests/1,000 just mean an epidemic that ran out of control, with an explosion of cases that demands high testing rates just to confirm the diagnosis of the seriously sick. This study also demonstrates that an early tracing strategy, with a high level of Tests/Case, reduces combined costs of testing and hospitalization dramatically. Therefore, the common claim that tracing strategies are unaffordable by poorer countries is incorrect. On the contrary, it is the most adequate, both from the economic and humanitarian points of view.

Projecting the COVID-19 curve parameters such as ending-lifecycle and cumulative cases are helpful in guiding the policy makers to mitigate the outbreak. However, overestimating these parameters may put the public and policy makers in a muddle. In this paper, an optimistic scenario is simulated, wherein the dynamics of the COVID-19 curve is allowed to spread to such an extent that the projections of the COVID-19 parameters do not take excessively high values. Based on this scenario, the ending life-cycle and cumulative cases for India and some of its states, are predicted. Our study, suggests that the fall of the peak amplitude (95%) of the major COVID-19 wave in India may take place by the 8th of September 2020 with a total count of 655000 cases. Simulation results, also indicate that Maharashtra, Tamil Nadu, Delhi, Gujarat, Uttar Pradesh, Bihar, Madhya Pradesh, and Rajasthan may end up with 263700, 18140, 50600, 21130, 24420, 44170, 27080, and 28200 cumulative cases respectively.

This paper analyses the trend in daily reported confirmed cases of COVID-19 in India using joinpoint regression analysis. The analysis reveals that there has been little impact of the nation-wide lockdown and subsequent extension on the progress of the COVID-19 pandemic in the country and there is no empirical evidence to suggest that relaxations under the third and the fourth phase of the lockdown have resulted in a spike in the reported confirmed cases. The analysis also suggests that if the current trend continues, in the immediate future, then the daily reported confirmed cases of COVID-19 in the country is likely to increase to 21 thousand by 15 June 2020 whereas the total number of confirmed cases of COVID-19 will increase to around 422 thousand. The analysis calls for a population-wide testing approach to check the increase in the reported confirmed cases of COVID-19.

BackgroundThe detection of SARS-CoV-2 RNA by real-time polymerase chain reaction (PCR) in respiratory samples from COVID-19 patients is not a direct indication of the presence of viable viruses. The isolation of SARS-CoV-2 in cell culture system however, can acts as surrogate marker of infectiousness. Cell culture based studies performed mostly with hospitalized and moderate/severe COVID-19 claims that no replication competent virus is found after 9 days of the symptoms onset in respiratory samples. Therefore, it is now recommended 10 days isolation before patient discharge. MethodsWe cell-cultured 29 SARS-COV-2 RT-PCR positive respiratory samples at the 10th day after the illness in Vero E6 cells. After two passages, cytopathic effect and cycle threshold (CT) lower than the obtained in the original sample were used to determine positivity. FindingsWe found viable particles in (7/29) 24% of samples tested. The positivity in cell culture was strongly associated (p<0.0001) to the low cycle thresholds in clinical samples (Ct <21). ConclusionThis data adds important knowledge to the current protocols for de-isolation of patients with non-hospitalized mild COVID-19.

IntroductionThe COVID-19 has emerged as a global concern for public health due to large scale outbreak. The number of confirmed cases has also been increased in India in past few weeks. The predictions for the COVID-19 can provide insights into the epidemiology of the disease, which helps policymakers to check health system capacities. MethodsWe obtained data on daily confirmed, recovered and deaths cases for a period of 21 days and have implemented the exponential growth model to predict the future cases for all the three components. The mathematical model was used to calculate the average reproduction number and herd immunity. We estimated the number of active cases till 30th of April. We have also tried to analyze the public health capacity to combat COVID-19 in India. ResultsIf the exponential growth in number of cases continue then the total number of active cases will be 2,49,635 until the end of April. The reproduction number for COVID-19 in India was found to be 2.56 and herd immunity as 61%. The cumulative cases predicted by the mathematical model was 1,20,203. DiscussionThis prediction provides an alarming situation for India in terms of public health preparedness. The number of tests is needed to increase to detect all the cases of COVID-19 in India. Though some serious preventive measures have been implemented, but India should be ready to face any sudden community outbreak.

The novel coronal virus has spread across more than 213 countries within the space of six months causing devastating public health hazard and monumental economic loss. In the absence of clinically approved pharmaceutical intervention, attentions are shifted to non-pharmaceutical controls to mitigate the burden of the novel pandemic. In this regard, a ten mutually exclusive compartmental mathematical model is developed to investigate possible effects of both pharmaceutical and non-pharmaceutical controls incorporating both private and governments quarantine and treatments. Several reproduction numbers were calculated and used to determine the impact of both control measures as well as projected benefits of social distancing, treatments and vaccination. We investigate and compare the possible impact of social distancing incorporating different levels of vaccination, with vaccination programme incorporating different levels of treatment. Using the officially published South African COVID-19 data, the numerical simulation shows that the community reproduction threshold will be 30 when there is no social distancing but will drastically reduced to 5 (about 83% reduction) when social distancing is enforced. Furthermore, when there is vaccination with perfect efficacy, the community reproduction threshold will be 4 which increases to 12 (about 67% increment) with-out vaccination. We also established that the implementation of both interventions is enough to curtail the spread of COVID-19 pandemic in South Africa which is in confirmation with the recommendation of the world health organization.