WikiJournal Preprints/What Impact has lockdown on SARS-CoV-2/COVID-19 incidence, prevalence and mortality during second wave of pandemic in 2021: - observational & statistical analysis of Bihar
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Dr Piyush Kumar. "COVID-19 incidence, prevalence and mortality during second wave of pandemic in 2021: - observational & statistical analysis of Bihar". WikiJournal Preprints. Wikidata Q110552435.
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Article information
Abstract
Methods: It’s a novel qualitative and quantitative (mixed) intervention (i.e. lockdown) research study. The information on the number of cases and deaths due to COVID-19 pandemic in Bihar was obtained from Health Department Bihar, Ministry of Health and Family Welfare, Government of India, and lockdown data were obtained from online websites as well. The period of study started 13 days before lockdown, first and second 13 days during lockdown, and 13 days after the lockdown to assess the impact of lockdown intervention on the incidence, prevalence and mortality due to the COVID-19 pandemic in Bihar. The data collected and analysed with Microsoft office and Stata software 15.1 for windows (64bit). The same will be used with Microsoft office in next version-3 of article with addition of two more period of observation i.e. one more 13 day period before lockdown and one more period after the lock down in order to observe 2 period of same duration before lockdown and 2 periods of same duration after lockdown. This period was under observation by the author. The version-3 will also discuss lockdown model of Bihar with criteria of inclusion and exclusion of lockdown detailed in the article as well as analysis summary for understanding in brief. Results: There is continuous decrease in Incidence/100000/ confirmed new cases, Incidence /100000/ confirmed new active cases, Incidence /100000/ new discharged cases, Prevalence/100000/active cases from beginning of pandemic during the period of observation while the other parameters have shown an increase during the observation periods. Conclusions: The findings indicate that 13 days after the lockdown, incidence, daily cases of COVID-19 and the growth of the disease showed a declined trend, but there was no significant decline in the prevalence and mortality. The study found that daily cases of SARS-COV-2 patients, and the growth factor results declined and the growth rate per day both declined to an impressive negative level in the case of the growth rate. The Bihar model of lockdown is of significance in reducing the daily new cases as well as it was found that, 13 days after the lockdown, the growth factor of the number of new daily cases decreased and the growth factor of new daily deaths was increased after the lockdown period. Keywords: COVID 19, Lockdown, Quarantine, Prevalence, Mortality, Epidemiological trends, 2021Bihar, active cases, confirmed cases,
Background edit
The delivery of health services is of greatest importance and major concern in India particularly populous states like Bihar with imperfect and inadequate resources, lack of modern infrastructure and enormous demand on healthcare structure. The Census 2011 calculated that Bihar has population of 10.41 Crores, an increase from figure of 8.30 Crores in 2001 census. As per 2011 census there were 54,278,157 male and 49,821,295 female respectively. As per projection of census, population of Bihar in 2021 is 13.12 Crore ([1])The SARS-CoV-2 pandemic had offered a challenge even for developed healthcare systems around the globe. A sense of panic engrossed the globe due to pandemic and the state of Bihar in India is not exclusion. The insufficient and inadequate healthcare resources including manpower, infrastructure, transportation (ambulance services) etc. have been largely utilized to tackle the situation of pandemic. This shift has tremendous effect of continuing various health programmes running formerly before the pandemic era ([2]).
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) popularly known as COVID-19 pandemic,
first found in Wuhan, China which had spread globally and causing morbidity, mortality as well as huge economic losses. The SARS-CoV-2/ Covid -19 pandemic are not over globally as well as in India and Bihar. The current healthcare system is burdened more with this new diseases added with previous NCD (non communicable diseases) & CD (communicable diseases). The First human case of this global pandemic was reported from Wuhan city of China in December 2019 ([3]).The first case ofcovid-19 in India was found in January 2020 and Bihar reported first COVID-19 case from Munger on 22 March 2020, a 38-year-old tested positive for COVID-19, he was also the first victim.
As of June 17, 2021, 07:33 GMT, covid-19 has involved 220 countries and has infected 177, 819, 445, people with a mortality of 3,849,051 deaths ([4]). The median incubation period for COVID-19 is usually 5.1 days, and may be up to 14 days. The incubation period of COVID-19 is very significant in establishing lockdown, monitoring, surveillance and control of the disease spread. The high contagious nature of COVID-19 has led to panic situation across the globe stopping entry and exit across different boundaries and even up to lowest administrative levels by implications of containment zones. The world-wide population has been under lockdown and quarantined in their homes at some point. The lockdown and quarantine methods have been implemented by many nations and states to control the spread of covid-19. The lockdown order in Bihar issued by Home Department dated 04/05/2021 announced lockdown from 05/05/2021 to 15/05/2021 and then extended up to 1 June, 2021, includes several restrictions such as isolation at homes, travel restrictions, and termination of all public events etc ([5]). The lockdown strategies in Bihar have been enforced like all over the world in order to prevent the COVID-19 infection from spreading even further. On comparing the pattern of transmission rates observed in few countries at posterior estimated change points, it is found that partial implementation of lockdown (in the United States), delayed planning in lockdown (Russia, United Kingdom, and France), and inadequate implementation of the lockdown (in India and Italy) were found to be mainly responsible for the spread of covid-19 infections ([6]).
Vaccines are known to effectively prevent a COVID-19 infection and reduce morbidity-mortality but there are multiple factors and obstacles in running smoothly the vaccination programme such as frequent change and unavailability of vaccines, guidelines, policies, interdisciplinary conflicts of medical sciences, mistrust, evil propaganda over Government data, lack of communication and health promotion in rural areas of India ([7]). Hence in current scenario of Bihar and most of states in India, public health measures such as lockdown, masks, quarantine, and social distancing appear to be the only ways to control the outbreak. Lockdown and quarantine can either be applied on a voluntary basis, or if seems necessary, can be legally forced by the authorities, and may be implemented at individual or community levels. The home quarantine, when scientifically and adequately applied and exercised according to covid-19 principles, guidelines, protocols and practices, can be quite effective for preventing the spread of covid-19 diseases. Globally, many countries have imposed a lockdown, quarantine period for over several days to months for this purpose. There are great economic concerns as well as question on the effectiveness and risks of long-term implementation of a lock-down and or quarantine. Keeping in view the rapid spread of COVID-19 cases and rise in mortality and morbidity in Bihar, the present study aimed to investigate the impact of lockdowns for 13 days before, first and second 13 days during lockdown and 13 days afterward on international epidemiological trends in the prevalence and mortality of COVID-19 cases.
Materials and methodology edit
It’s a novel qualitative and quantitative (mixed) intervention (i.e. lockdown) research study. The present observational study was conducted by the author during the period of May–June 2021. The data on the trends in the incidence, prevalence and mortality due to COVID-19 outbreak in Bihar were collected on daily basis from Health Department, Bihar as well as Ministry of Health and Family Welfare, Government of India also matched with online sources available in Google search. The daily reports on COVID-19 published by the Health Department, Bihar as well as Ministry of Health and Family Welfare, Government of India through website, twitter etc. were care-fully reviewed and data were collected . The lockdown data were obtained time to time from concerned authorities. The population data of Bihar was obtained from the census2011 publications. Data of all the 38 districts of Bihar have been collected and analysed as well as calculation for incidence, prevalence and mortality was done and presented as table (see table 1,2,3,4,5,6,7,8,9,10,11 and Figure / chart 1) and chart in this article.
The growth factor I considered is as a ratio equals to cases on last day of each of four observations divided by cases on the first day of observation (see table-9). A growth factor of more than 1.0 indicates an increasing pattern of prevalence, whereas values between below 1.0 show a declining pattern. A positive growth factor indicates exponential growth in the number of cases and a negative growth factor for the period indicates exponential decay in the number of new cases. A negative growth rate per observation period means an epidemic is coming under control because in that case, the number of new cases each day will be decreasing and heading in a direction toward no new cases in a day. The collected data were properly recorded and analysed because the pandemic has been changing numbers daily. I analysed the impact of lockdown on the growth factor, incidence, prevalence and mortality due to COVID-19 outbreak in Bihar, India by establishing an calculating-analysing association between the numbers, 13 days before, 26 days during (divided into two equal parts 13 days each, termed first 13 and second 13) and 13 days after the end of the lockdown period on 01/06/2021.
Statistical analysis edit
The data were recorded, calculated and analysed with Microsoft office and Stata software for analysis, and the output-results were expressed in numbers and percentages presented in tables 1,2,3,4,5,6,7,8,9,10,11. The average of confirmed new cases/new active cases/new cured cases/new death, prevalence and mortality of cases were calculated. The growth factor, by which quantity multiplies itself over time; here 13th day cases divided by cases on the first day was calculated. The statistical analysis is detailed below in table numbers A, B, C, D, and E in results section.
Results edit
The total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths due to covid-2019 pandemic 13 days before lockdown are presented in Table 1. The total number of laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths due to Covid-2019 pandemic 13 days before lockdown are presented in Table 2.
The impact of the lockdown on the epidemiological trends of covid-19 is presented in Tables 3, 4, 5, and 6. The epidemiological trends after lockdown are presented in tables 7 and 8. Table 9 shows the Growth Factor for Number of laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths/ Confirmed cases / Active Cases/ Cured/Discharged/ and deaths due to Covid-2019 pandemic. Table 10 presents the Prevalence/Incidence/Mortality of Number of laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths/ Confirmed cases / Active Cases/ Cured/Discharged/ and deaths due to Covid-2019 pandemic. Table 11 presents the average number of confirmed new cases/new active cases/new cured cases/new death, at 13 days before, 26 days during, and 13 days after the lockdown in Bihar, India and correlations were established.
Table 1 Bihar- Total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic 13 days before lockdown since beginning of pandemic
| Date | Region | Total Confirmed Cases | Total Active Cases | Total Cured | Total Death | |
| 22/04/2021 | Bihar | 354281 | 63747 | 288637 | 1897 | |
| 23/04/2021 | Bihar | 365770 | 69869 | 293945 | 1956 | |
| 24/04/2021 | Bihar | 378442 | 76420 | 300012 | 2010 | |
| 25/04/2021 | Bihar | 390801 | 81961 | 306753 | 2087 | |
| 26/04/2021 | Bihar | 403596 | 87155 | 314286 | 2155 | |
| 27/04/2021 | Bihar | 415397 | 89661 | 323514 | 2222 | |
| 28/04/2021 | Bihar | 428001 | 94276 | 331418 | 2307 | |
| 29/04/2021 | Bihar | 441375 | 98748 | 340236 | 2391 | |
| 30/04/2021 | Bihar | 454464 | 100822 | 351162 | 2480 | |
| 1/5/2021 | Bihar | 470317 | 105401 | 362356 | 2560 | |
| 2/5/2021 | Bihar | 484106 | 108203 | 373261 | 2642 | |
| 3/5/2021 | Bihar | 497640 | 109946 | 384955 | 2739 | |
| 4/5/2021 | Bihar | 509047 | 107668 | 398558 | 2821 | |
| Total | 509047 | 107668 | 398558 | 2821 |
Table 2 Bihar- Number of laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic 13 days before lockdown
| Date | Confirmed New Cases | New Active Cases | New Cured | New Death | Population-2011
Census |
| 22/04/2021 | 12222 | 7392 | 4774 | 56 | 104099452 |
| 23/04/2021 | 11489 | 6122 | 5308 | 59 | 104099452 |
| 24/04/2021 | 12672 | 6551 | 6067 | 54 | 104099452 |
| 25/04/2021 | 12359 | 5541 | 6741 | 77 | 104099452 |
| 26/04/2021 | 12795 | 5194 | 7533 | 68 | 104099452 |
| 27/04/2021 | 11801 | 2506 | 9228 | 67 | 104099452 |
| 28/04/2021 | 12604 | 4615 | 7904 | 85 | 104099452 |
| 29/04/2021 | 13374 | 4472 | 8818 | 84 | 104099452 |
| 30/04/2021 | 13089 | 2074 | 10926 | 89 | 104099452 |
| 1/5/2021 | 15853 | 4579 | 11194 | 80 | 104099452 |
| 2/5/2021 | 13789 | 2802 | 10905 | 82 | 104099452 |
| 3/5/2021 | 13534 | 1743 | 11694 | 97 | 104099452 |
| 4/5/2021 | 11407 | -2278 | 13603 | 82 | 104099452 |
| Total | 166988 | 51313 | 114695 | 980 |
Table-A-The statistical analysis (Table-A) of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during 13 days before lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during 13 days before lockdown is as follow: see table
Note:-Obs-observation, Std. Dev-standard deviation, Min-minimum, Max-maximum, Totalconfi~s-total confirmed cases, newconfirm~s- new confirm cases, newactivec~s- new active cases,
Summary – 13 days before lockdown Table-A
Variable | Obs Mean Std. Dev. Min Max
Totalconfi~s | 13 430249 50885.21 354281 509047
Totalactiv~s | 13 91836.69 15270.73 63747 109946
Totalcured | 13 336084.1 35883.66 288637 398558
Totaldeath | 13 2328.231 305.0162 1897 2821
Newconfirm~s | 13 12845.23 1171.347 11407 15853
Newactivec~s | 13 3947.154 2567.432 -2278 7392
New cured | 13 8822.692 2720.64 4774 13603
New death | 13 75.38462 13.40733 54 97
Detailed summary-13 days before lockdown- Table-A
Total Confirmed Cases
Percentiles Smallest
1% 354281 354281
5% 354281 365770
10% 365770 378442 Obs 13
25% 390801 390801 Sum of Wgt. 13
50% 428001 Mean 430249
Largest Std. Dev. 50885.21
75% 470317 470317
90% 497640 484106 Variance 2.59e+09
95% 509047 497640 Skewness .0673399
99% 509047 509047 Kurtosis 1.767969
Total Active Cases-13 days before lockdown
Percentiles Smallest
1% 63747 63747
5% 63747 69869
10% 69869 76420 Obs 13
25% 81961 81961 Sum of Wgt. 13
50% 94276 Mean 91836.69
Largest Std. Dev. 15270.73
75% 105401 105401
90% 108203 107668 Variance 2.33e+08
95% 109946 108203 Skewness -.4785806 Table-A
99% 109946 109946 Kurtosis 2.00337
Total Cured-13 days before lockdown Table-A
Percentiles Smallest
1% 288637 288637
5% 288637 293945
10% 293945 300012 Obs 13
25% 306753 306753 Sum of Wgt. 13
50% 331418 Mean 336084.1
Largest Std. Dev. 35883.66
75% 362356 362356
90% 384955 373261 Variance 1.29e+09
95% 398558 384955 Skewness .3140853
99% 398558 398558 Kurtosis 1.86663
Total Death-13 days before lockdown
Percentiles Smallest
1% 1897 1897
5% 1897 1956
10% 1956 2010 Obs 13
25% 2087 2087 Sum of Wgt. 13
50% 2307 Mean 2328.231
Largest Std. Dev. 305.0162
75% 2560 2560
90% 2739 2642 Variance 93034.86 Table-A
95% 2821 2739 Skewness .157749
99% 2821 2821 Kurtosis 1.762751
New Confirmed Cases-13 days before lockdown Table-A
Percentiles Smallest
1% 11407 11407
5% 11407 11489
10% 11489 11801 Obs 13
25% 12222 12222 Sum of Wgt. 13
50% 12672 Mean 12845.23
Largest Std. Dev. 1171.347
75% 13374 13374
90% 13789 13534 Variance 1372054
95% 15853 13789 Skewness 1.163319
99% 15853 15853 Kurtosis 4.412122
New Active Cases-13 days before lockdown
Percentiles Smallest
1% -2278 -2278
5% -2278 1743
10% 1743 2074 Obs 13
25% 2506 2506 Sum of Wgt. 13
50% 4579 Mean 3947.154
Largest Std. Dev. 2567.432
75% 5541 5541
90% 6551 6122 Variance 6591705 Table-A
95% 7392 6551 Skewness -.9610262
99% 7392 7392 Kurtosis 3.661296
New Cured-13 days before lockdown Table-A
Percentiles Smallest
1% 4774 4774
5% 4774 5308
10% 5308 6067 Obs 13
25% 6741 6741 Sum of Wgt. 13
50% 8818 Mean 8822.692
Largest Std. Dev. 2720.64
75% 10926 10926
90% 11694 11194 Variance 7401884
95% 13603 11694 Skewness .0947236
99% 13603 13603 Kurtosis 1.913701
New Death-13 days before lockdown
Percentiles Smallest
1% 54 54
5% 54 56
10% 56 59 Obs 13
25% 67 67 Sum of Wgt. 13
50% 80 Mean 75.38462
Largest Std. Dev. 13.40733
75% 84 84
90% 89 85 Variance 179.7564 Table-A
95% 97 89 Skewness -.2742626
99% 97 97 Kurtosis 1.959424
Table statistical analysis- total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( mean max range var count min sd cv )- 13 days before lockdown
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath Table-A
mean | 430249 91836.69 336084.1 2328.231 12845.23 3947.154 8822.692 75.38462
max | 509047 109946 398558 2821 15853 7392 13603 97
range | 154766 46199 109921 924 4446 9670 8829 43
variance | 2.59e+09 2.33e+08 1.29e+09 93034.86 1372054 6591705 7401884 179.7564
N | 13 13 13 13 13 13 13 13
min | 354281 63747 288637 1897 11407 -2278 4774 54
sd | 50885.21 15270.73 35883.66 305.0162 1171.347 2567.432 2720.64 13.40733
cv | .1182692 .1662813 .1067699 .1310077 .0911893 .6504514 .3083685 .1778523
tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( se mean kurtosis iqr p25 skewness median p1 p99 )- 13 days before lockdown
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath
se(mean) | 14113.02 4235.338 9952.337 84.59626 324.8732 712.0774 754.5699 3.718523
kurtosis | 1.767969 2.00337 1.86663 1.762751 4.412122 3.661296 1.913701 1.959424
iqr | 79516 23440 55603 473 1152 3035 4185 17
p25 | 390801 81961 306753 2087 12222 2506 6741 67
skewness | .0673399 -.4785806 .3140853 .157749 1.163319 -.9610262 .0947236 -.2742626
p50 | 428001 94276 331418 2307 1 2672 4579 8818 80
p1 | 354281 63747 288637 1897 11407 -2278 4774 54
p99 | 509047 109946 398558 2821 15853 7392 13603 97 Table-A
Table 3 Bihar- Total Number of laboratory-Confirmed cases / Active Cases/ Cured/Discharged/ and deaths date wise due to Covid-2019 pandemic-first 13 days of lockdown since beginning of pandemic
| Date | Region | Total Confirmed Cases | Total Active Cases | Total Cured | Total Death |
| 5/5/2021 | Bihar | 523841 | 110431 | 410484 | 2926 |
| 6/5/2021 | Bihar | 538677 | 113480 | 422210 | 2987 |
| 7/5/2021 | Bihar | 553803 | 115152 | 435574 | 3077 |
| 8/5/2021 | Bihar | 567269 | 115067 | 449063 | 3139 |
| 9/5/2021 | Bihar | 580217 | 112977 | 464025 | 3215 |
| 10/5/2021 | Bihar | 591476 | 110805 | 477389 | 3282 |
| 11/5/2021 | Bihar | 601650 | 105104 | 493189 | 3357 |
| 12/5/2021 | Bihar | 612570 | 102100 | 507041 | 3429 |
| 13/05/2021 | Bihar | 622433 | 99624 | 519306 | 3503 |
| 14/05/2021 | Bihar | 622433 | 99624 | 519306 | 3503 |
| 15/05/2021 | Bihar | 630185 | 96278 | 530314 | 3593 |
| 16/05/2021 | Bihar | 645015 | 82487 | 558785 | 3743 |
| 17/05/2021 | Bihar | 651909 | 75090 | 572987 | 3832 |
| Total | 651909 | 75090 | 572987 | 3832 |
Table 4 Bihar- Number of laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic-first 13 days of lockdown
| Date | New Confirmed Cases | New Active Cases | New Cured | New Death | Population-2011
Census |
| 5/5/2021 | 14794 | 2763 | 11926 | 105 | 104099452 |
| 6/5/2021 | 14836 | 3049 | 11726 | 61 | 104099452 |
| 7/5/2021 | 15126 | 1672 | 13364 | 90 | 104099452 |
| 8/5/2021 | 13466 | -85 | 13489 | 62 | 104099452 |
| 9/5/2021 | 12948 | -2090 | 14962 | 76 | 104099452 |
| 10/5/2021 | 11259 | -2172 | 13364 | 67 | 104099452 |
| 11/5/2021 | 10174 | -5701 | 15800 | 75 | 104099452 |
| 12/5/2021 | 10920 | -3004 | 13852 | 72 | 104099452 |
| 13/05/2021 | 9863 | -2476 | 12265 | 74 | 104099452 |
| 14/05/2021 | 0 | 0 | 0 | 0 | 104099452 |
| 15/05/2021 | 7752 | -3346 | 11008 | 90 | 104099452 |
| 16/05/2021 | 14830 | -13791 | 28471 | 150 | 104099452 |
| 17/05/2021 | 6894 | -7397 | 14202 | 89 | 104099452 |
| Total | 142862 | -32578 | 174429 | 1011 |
The statistical analysis of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days of lockdown is as follow: Table-B
Summary of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days of lockdown is as follow:
Variable | Obs Mean Std. Dev. Min Max
totalconfi~s | 13 595498.3 40585.3 523841 651909
totalactiv~s | 13 102939.9 12555.59 75090 115152
totalcured | 13 489205.6 51351.34 410484 572987
totaldeath | 13 3352.769 281.7023 2926 3832
newconfirm~s | 13 10989.38 4292.763 0 15126
newactivec~s | 13 -2506 4572.906 -13791 3049
newcured | 13 13417.62 5970.299 0 28471
newdeath | 13 77.76923 33.08613 0 150
detailed statistical analysis of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days of lockdown is as follow: Table-B
Total Confirmed Cases
Percentiles Smallest
1% 523841 523841
5% 523841 538677
10% 538677 553803 Obs 13
25% 567269 567269 Sum of Wgt. 13 Table-B
50% 601650 Mean 595498.3
Largest Std. Dev. 40585.3
75% 622433 622433
90% 645015 630185 Variance 1.65e+09
95% 651909 645015 Skewness -.3413298
99% 651909 651909 Kurtosis 1.970721
Total Active Cases
Percentiles Smallest
1% 75090 75090
5% 75090 82487
10% 82487 96278 Obs 13
25% 99624 99624 Sum of Wgt. 13
50% 105104 Mean 102939.9
Largest Std. Dev. 12555.59
75% 112977 112977
90% 115067 113480 Variance 1.58e+08
95% 115152 115067 Skewness -1.043925 Table-B
99% 115152 115152 Kurtosis 3.095616
Total Cured
Percentiles Smallest
1% 410484 410484
5% 410484 422210
10% 422210 435574 Obs 13
25% 449063 449063 Sum of Wgt. 13 Table-B
50% 493189 Mean 489205.6
Largest Std. Dev. 51351.34
75% 519306 519306
90% 558785 530314 Variance 2.64e+09
95% 572987 558785 Skewness .0189448
99% 572987 572987 Kurtosis 1.910434
Total Death
Percentiles Smallest
1% 2926 2926
5% 2926 2987
10% 2987 3077 Obs 13
25% 3139 3139 Sum of Wgt. 13
50% 3357 Mean 3352.769
Largest Std. Dev. 281.7023
75% 3503 3503
90% 3743 3593 Variance 79356.19
95% 3832 3743 Skewness .1171762 Table-B
99% 3832 3832 Kurtosis 2.00191
New Confirmed Cases
Percentiles Smallest
1% 0 0
5% 0 6894
10% 6894 7752 Obs 13
25% 9863 9863 Sum of Wgt. 13 Table-B
50% 11259 Mean 10989.38
Largest Std. Dev. 4292.763
75% 14794 14794
90% 14836 14830 Variance 1.84e+07
95% 15126 14836 Skewness -1.282402
99% 15126 15126 Kurtosis 4.245312
New Active Cases
Percentiles Smallest
1% -13791 -13791
5% -13791 -7397
10% -7397 -5701 Obs 13
25% -3346 -3346 Sum of Wgt. 13
50% -2172 Mean -2506
Largest Std. Dev. 4572.906
75% 0 0
90% 2763 1672 Variance 2.09e+07
95% 3049 2763 Skewness -1.058352 Table-B
99% 3049 3049 Kurtosis 3.921874
New Cured
Percentiles Smallest
1% 0 0
5% 0 11008
10% 11008 11726 Obs 13
25% 11926 11926 Sum of Wgt. 13 Table-B
50% 13364 Mean 13417.62
Largest Std. Dev. 5970.299
75% 14202 14202
90% 15800 14962 Variance 3.56e+07
95% 28471 15800 Skewness .4033586
99% 28471 28471 Kurtosis 5.957854
New Death
Percentiles Smallest
1% 0 0
5% 0 61
10% 61 62 Obs 13
25% 67 67 Sum of Wgt. 13
50% 75 Mean 77.76923
Largest Std. Dev. 33.08613
75% 90 90
90% 105 90 Variance 1094.692
95% 150 105 Skewness -.1877358 Table-B
99% 150 150 Kurtosis 4.864022
tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( mean sum mean mean count mean mean mean ) of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days of lockdown is as follow:
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath
mean | 595498.3 102939.9 489205.6 3352.769 10989.38 -2506 13417.62 77.76923
sum | 7741478 1338219 6359673 43586 142862 -32578 174429 1011 Table-B
mean | 595498.3 102939.9 489205.6 3352.769 10989.38 -2506 13417.62 77.76923
mean | 595498.3 102939.9 489205.6 3352.769 10989.38 -2506 13417.62 77.76923
N | 13 13 13 13 13 13 13 13
mean | 595498.3 102939.9 489205.6 3352.769 10989.38 -2506 13417.62 77.76923
mean | 595498.3 102939.9 489205.6 3352.769 10989.38 -2506 13417.62 77.76923
mean | 595498.3 102939.9 489205.6 3352.769 10989.38 -2506 13417.62 77.76923
tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( mean sum min sd count max range var ) of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days of lockdown is as follow:
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath
mean | 595498.3 102939.9 489205.6 3352.769 10989.38 -2506 13417.62 77.76923
sum | 7741478 1338219 6359673 43586 142862 -32578 174429 1011
min | 523841 75090 410484 2926 0 -13791 0 0
sd | 40585.3 12555.59 51351.34 281.7023 4292.763 4572.906 5970.299 33.08613
N | 13 13 13 13 13 13 13 13
max | 651909 115152 572987 3832 15126 3049 28471 150
range | 128068 40062 162503 906 15126 16840 28471 150 Table-B
variance | 1.65e+09 1.58e+08 2.64e+09 79356.19 1.84e+07 2.09e+07 3.56e+07 1094.692
. tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( cv skewness median p1 semean kurtosis iqr p99 ) of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days of lockdown is as follow: cv-coefficient of variance, se-standard error,
Table-B
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath
cv | .0681535 .1219701 .1049688 .0840208 .3906282 -1.824783 .4449598 .4254399
skewness | -.3413298 -1.043925 .0189448 .1171762 -1.282402 -1.058352 .4033586 -.1877358
p50 | 601650 105104 493189 3357 11259 -2172 13364 75
p1 | 523841 75090 410484 2926 0 -13791 0 0
se(mean) | 11256.34 3482.294 14242.3 78.13016 1190.598 1268.296 1655.863 9.176443
kurtosis | 1.970721 3.095616 1.910434 2.00191 4.245312 3.921874 5.957854 4.864022
iqr | 55164 13353 70243 364 4931 3346 2276 23
p99 | 651909 115152 572987 3832 15126 3049 28471 150
Table 5 Bihar- Total Number of laboratory-Confirmed cases / Active Cases/ Cured/Discharged/ and deaths date wise due to Covid-2019 pandemic-second 13 days of lockdown since beginning of pandemic
| Date | Region | Total Confirmed Cases | Total Active Cases | Total Cured | Total Death |
| 18/05/2021 | Bihar | 657829 | 69698 | 584203 | 3928 |
| 19/05/2021 | Bihar | 664115 | 64699 | 595377 | 4039 |
| 20/05/2021 | Bihar | 670174 | 58611 | 607420 | 4143 |
| 21/05/2021 | Bihar | 676045 | 54407 | 617397 | 4241 |
| 22/05/2021 | Bihar | 681199 | 49312 | 627548 | 4339 |
| 23/05/2021 | Bihar | 685574 | 44908 | 636224 | 4442 |
| 24/05/2021 | Bihar | 689576 | 40692 | 644335 | 4549 |
| 25/05/2021 | Bihar | 692420 | 37943 | 649835 | 4642 |
| 26/05/2021 | Bihar | 695726 | 35130 | 655850 | 4746 |
| 27/05/2021 | Bihar | 698329 | 30993 | 662491 | 4845 |
| 28/05/2021 | Bihar | 700897 | 28448 | 667506 | 4943 |
| 30/05/2021 | Bihar | 704173 | 21085 | 678036 | 5052 |
| 31/05/2021 | Bihar | 705648 | 18378 | 682166 | 5104 |
| Total | 705648 | 18378 | 682166 | 5104 |
Table 6 Bihar- Number of laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic-second 13 days of lockdown
| Date | New Confirmed Cases | New Active Cases | New Cured | New Death | Population-2011
Census |
| 18/05/2021 | 5920 | -5392 | 11216 | 96 | 104099452 |
| 19/05/2021 | 6286 | -4999 | 11174 | 111 | 104099452 |
| 20/05/2021 | 6059 | -6088 | 12043 | 104 | 104099452 |
| 21/05/2021 | 5871 | -4204 | 9977 | 98 | 104099452 |
| 22/05/2021 | 5154 | -5095 | 10151 | 98 | 104099452 |
| 23/05/2021 | 4375 | -4404 | 8676 | 103 | 104099452 |
| 24/05/2021 | 4002 | -4216 | 8111 | 107 | 104099452 |
| 25/05/2021 | 2844 | -2749 | 5500 | 93 | 104099452 |
| 26/05/2021 | 3306 | -2813 | 6015 | 104 | 104099452 |
| 27/05/2021 | 2603 | -4137 | 6641 | 99 | 104099452 |
| 28/05/2021 | 2568 | -2545 | 5015 | 98 | 104099452 |
| 30/05/2021 | 3276 | -7363 | 10530 | 109 | 104099452 |
| 31/05/2021 | 1475 | -2707 | 4130 | 52 | 104099452 |
| Total | 53739 | -56712 | 109179 | 1272 |
The statistical analysis of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during second 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during second 13 days of lockdown is as follow: Table-C
Summary of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during second 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during second 13 days of lockdown is as follow:
Variable | Obs Mean Std. Dev. Min Max Table-C
totalconfi~s | 13 686285 15500.33 657829 705648
totalactiv~s | 13 42638.77 16161.98 18378 69698
totalcured | 13 639106.8 31211.22 584203 682166
totaldeath | 13 4539.462 388.4962 3928 5104
newconfirm~s | 13 4133.769 1597.186 1475 6286
newactivec~s | 13 -4362.462 1447.106 -7363 -2545
newcured | 13 8398.385 2677.519 4130 12043
newdeath | 13 97.84615 14.75831 52 111
. tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( mean sum min sd count max range var ) of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during second 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during second 13 days of lockdown is as follow:
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath
mean | 686285 42638.77 639106.8 4539.462 4133.769 -4362.462 8398.385 97.84615
sum | 8921705 554304 8308388 59013 53739 -56712 109179 1272
min | 657829 18378 584203 3928 1475 -7363 4130 52
sd | 15500.33 16161.98 31211.22 388.4962 1597.186 1447.106 2677.519 14.75831
N | 13 13 13 13 13 13 13 13
max | 705648 69698 682166 5104 6286 -2545 12043 111
range | 47819 51320 97963 1176 4811 4818 7913 59
variance | 2.40e+08 2.61e+08 9.74e+08 150929.3 2551004 2094115 7169109 217.8077
. tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( cv skewness median p1 semean kurtosis iqr p99 ) of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during second 13 days of lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during second 13 days of lockdown is as follow:
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath Table-C
cv | .0225859 .3790442 .0488357 .085582 .3863753 -.3317177 .3188136 .1508318
skewness | -.4743759 .1499369 -.3199312 -.0490504 -.009441 -.4412226 -.2198114 -2.46753
p50 | 689576 40692 644335 4549 4002 -4216 8676 99
p1 | 657829 18378 584203 3928 1475 -7363 4130 52
se(mean) | 4299.019 4482.526 8656.435 107.7494 442.9797 401.355 742.6102 4.093219
kurtosis | 2.025863 1.963662 1.975774 1.762036 1.676102 2.521116 1.599268 8.514757
iqr | 22284 23414 45094 604 3027 2282 4515 6
p99 | 705648 69698 682166 5104 6286 -2545 12043 111
Table 7 Bihar- Total Number of laboratory-Confirmed cases / Active Cases/ Cured/Discharged/ and deaths date wise due to Covid-2019 pandemic-first 13 days after lockdown since beginning of pandemic
| Date | Region | Total Confirmed Cases | Total Active Cases | Total Cured | Total Death |
| 2/6/2021 | Bihar | 707935 | 14251 | 688462 | 5222 |
| 3/6/2021 | Bihar | 709093 | 12591 | 691234 | 5268 |
| 4/6/2021 | Bihar | 710199 | 11431 | 693472 | 5296 |
| 5/6/2021 | Bihar | 711190 | 10309 | 695562 | 5319 |
| 6/6/2021 | Bihar | 712197 | 9628 | 697229 | 5340 |
| 7/6/2021 | Bihar | 713117 | 8708 | 699028 | 5381 |
| 8/6/2021 | Bihar | 713879 | 8231 | 700224 | 5424 |
| 9/6/2021 | Bihar | 714590 | 7898 | 701234 | 5458 |
| 10/6/2021 | Bihar | 715179 | 4516 | 701234 | 9429 |
| 11/6/2021 | Bihar | 715730 | 5044 | 701234 | 9452 |
| 12/6/2021 | Bihar | 716296 | 5596 | 701234 | 9466 |
| 13/06/2021 | Bihar | 716728 | 5701 | 701543 | 9484 |
| 14/06/2021 | Bihar | 717215 | 5312 | 702411 | 9492 |
| Total | 717215 | 5312 | 702411 | 9492 |
Table 8 Bihar- Number of laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic- first 13 days after lockdown
| Date | New Confirmed Cases | New Active Cases | New Cured | New Death | Population-2011
Census |
| 2/6/2021 | 2287 | -4127 | 6296 | 118 | 104099452 |
| 3/6/2021 | 1158 | -1660 | 2772 | 46 | 104099452 |
| 4/6/2021 | 1106 | -1160 | 2238 | 28 | 104099452 |
| 5/6/2021 | 991 | -1122 | 2090 | 23 | 104099452 |
| 6/6/2021 | 1007 | -681 | 1667 | 21 | 104099452 |
| 7/6/2021 | 920 | -920 | 1799 | 41 | 104099452 |
| 8/6/2021 | 762 | -477 | 1196 | 43 | 104099452 |
| 9/6/2021 | 711 | -333 | 1010 | 34 | 104099452 |
| 10/6/2021 | 589 | -3382 | 0 | 3971 | 104099452 |
| 11/6/2021 | 551 | 528 | 0 | 23 | 104099452 |
| 12/6/2021 | 566 | 552 | 0 | 14 | 104099452 |
| 13/06/2021 | 432 | 105 | 309 | 18 | 104099452 |
| 14/06/2021 | 487 | -389 | 868 | 8 | 104099452 |
| Total | 11567 | -13066 | 20245 | 4388 |
The statistical analysis of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days after lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days after lockdown is as follow: Table-D
Summary of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days after lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days after lockdown is as follow:
Variable | Obs Mean Std. Dev. Min Max
totalconfi~s | 13 713334.5 3017.647 707935 717215 Table-D
totalactiv~s | 13 8401.231 3129.753 4516 14251
totalcured | 13 698007.8 4505.924 688462 702411
totaldeath | 13 6925.462 2090.263 5222 9492
newconfirm~s | 13 889.7692 485.2812 432 2287 Table-D
newactivec~s | 13 -1005.077 1387.21 -4127 552
newcured | 13 1557.308 1695.272 0 6296
newdeath | 13 337.5385 1092.067 8 3971
. tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( mean sum min sd count max range var ) of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days after lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days after lockdown is as follow:
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath
mean | 713334.5 8401.231 698007.8 6925.462 889.7692 -1005.077 1557.308 337.5385
sum | 9273348 109216 9074101 90031 11567 -13066 20245 4388
min | 707935 4516 688462 5222 432 -4127 0 8
sd | 3017.647 3129.753 4505.924 2090.263 485.2812 1387.21 1695.272 1092.067
N | 13 13 13 13 13 13 13 13
max | 717215 14251 702411 9492 2287 552 6296 3971
range | 9280 9735 13949 4270 1855 4679 6296 3963
variance | 9106195 9795356 2.03e+07 4369198 235497.9 1924351 2873947 1192610
tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( cv skewness iqr p50 semean kurtosis p1 p99 ) of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic during first 13 days after lockdown since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic during first 13 days after lockdown is as follow:
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath
cv | .0042303 .3725351 .0064554 .3018229 .5454012 -1.380203 1.088591 3.235384
skewness | -.411078 .4031437 -.9606283 .4719014 1.890376 -1.126724 1.688896 3.171883
iqr | 4540 4713 5672 4133 441 827 1781 22
p50 | 713879 8231 700224 5424 762 -681 1196 28
se(mean) | 836.9448 868.0374 1249.719 579.7346 134.5928 384.7428 470.1838 302.8848
kurtosis | 1.934036 2.01356 2.597036 1.22643 6.385639 3.424112 5.761439 11.06952
p1 | 707935 4516 688462 5222 432 -4127 0 8
p99 | 717215 14251 702411 9492 2287 552 6296 3971 Table-D
The statistical analysis from first 13 days before lockdown upto first 13 days (total 52 days observation) after lockdown of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic is as follow: Table-E
Summary first 13 days before lockdown upto first 13 days (total 52 days observation) after lockdown of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic
Variable | Obs Mean Std. Dev. Min Max Table-E
totalconfi~s | 52 606341.7 116347.2 354281 717215
totalactiv~s | 52 61454.15 40465.07 4516 115152
totalcured | 52 540601.1 145882.3 288637 702411
totaldeath | 52 4286.481 2023.695 1897 9492
newconfirm~s | 52 7214.538 5444.66 0 15853
newactivec~s | 52 -981.5962 4137.047 -13791 7392
newcured | 52 8049 5546.55 0 28471
newdeath | 52 147.1346 541.6311 0 3971
tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( mean sum min sd count max range var ) first 13 days before lockdown upto first 13 days (total 52 days observation) after lockdown of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath
mean | 606341.7 61454.15 540601.1 4286.481 7214.538 -981.5962 8049 147.1346
sum | 3.15e+07 3195616 2.81e+07 222897 375156 -51043 418548 7651
min | 354281 4516 288637 1897 0 -13791 0 0 Table-E
sd | 116347.2 40465.07 145882.3 2023.695 5444.66 4137.047 5546.55 541.6311
N | 52 52 52 52 52 52 52 52
max | 717215 115152 702411 9492 15853 7392 28471 3971
range | 362934 110636 413774 7595 15853 21183 28471 3971
variance | 1.35e+10 1.64e+09 2.13e+10 4095340 2.96e+07 1.71e+07 3.08e+07 293364.2
tab stat, total confirmed cases, total active cases, total cured, totaldeath, new confirmed cases, new active cases, newcured, new death, statistics ( cv skewness median p1 semean kurtosis iqr p99 ) first 13 days before lockdown upto first 13 days (total 52 days observation) after lockdown of total number of laboratory-confirmed cases / active cases/ cured/discharged/ and deaths date wise due to covid-2019 pandemic since beginning of pandemic & laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths per day date wise due to Covid-2019 pandemic
stats | totalc~s totala~s totalc~d totald~h newcon~s newact~s newcured newdeath
cv | .1918838 .6584594 .2698521 .472111 .7546789 -4.214612 .689098 3.681194
skewness | -.8165001 -.1422879 -.3861551 1.404477 .0798102 -.1763979 .7000481 6.962723
p50 | 654869 67198.5 578595 3880 6172.5 -1141 8393.5 78.5
p1 | 354281 4516 288637 1897 0 -13791 0 0
se(mean) | 16134.45 5611.495 20230.24 280.636 755.0385 573.7052 769.1681 75.11072
kurtosis | 2.26633 1.450324 1.639856 4.574773 1.389889 3.470068 4.69367 49.66685
iqr | 190347.5 83908.5 280793 2289.5 11321.5 5663 8259 45
p99 | 717215 115152 702411 9492 15853 7392 28471 3971 Table-E
Table 9 Bihar-Growth Factor- Number of laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths/ Confirmed cases / Active Cases/ Cured/Discharged/ and deaths due to Covid-2019 pandemic
| Prevalence/Incidence/Mortality | Growth Factor First 13 days before lockdown | Growth Factor First 13 day of lockdown | Growth Factor Second 13 day of lockdown | Growth Factor First 13 day after lockdown |
| confirmed new cases | 0.933316969 | 0.46599973 | 0.249155405 | 0.21294272 |
| confirmed new active cases | -0.308170996 | -2.677162505 | 0.502040059 | 0.09425733 |
| new discharged cases | 2.849392543 | 1.190843535 | 0.368223966 | 0.137865311 |
| new death | 1.464285714 | 0.847619048 | 0.541666667 | 0.06779661 |
| confirmed cases basis-
Observation on 05/05/20 |
1.436845329 | 1.244478764 | 1.072692143 | 1.013108548 |
| active cases basis-
Observation on 05/05/20 |
1.688989286 | 0.679972109 | 0.26368045 | 0.372745772 |
| discharged cases basis-
Observation on 05/05/20 |
1.380827822 | 1.395881447 | 1.167686575 | 1.020261104 |
| Prevalence basis-
Observation on 05/05/20 |
1.487085 | 1.309638 | 1.299389 | 1.817694 |
| Mortality basis-
Observation on 05/05/20 |
1.487085 | 1.309638 | 1.299389 | 1.817694 |
| Total Mortality basis-
Observation on 05/05/20 |
1.464285714 | 0.847619048 | 0.541666667 | 0.06779661 |
Table 10 Bihar- Prevalence/Incidence/Mortality - Number of laboratory-Confirmed New cases / New Active Cases/ New Cured/ New Discharged/ and New deaths/ Confirmed cases / Active Cases/ Cured/Discharged/ and deaths due to Covid-2019 pandemic
| Prevalence/Incidence/Mortality | First 13 days before lockdown | First 13 day of lockdown | Second 13 day of lockdown | First 13 day after lockdown | Final increase or decrease |
| Incidence/100000/ confirmed new cases | 160.4119876 | 137.2360731 | 51.62275014 | 11.11148981 | decrease |
| Incidence /100000/ confirmed new active cases | 49.29228638 | -31.29507348 | -54.47867295 | -12.55145896 | decrease |
| Incidence /100000/ new discharged cases | 110.1782937 | 167.5599599 | 104.8795146 | 19.44774887 | decrease |
| Incidence /100000/ new death | 0.941407453 | 0.971186669 | 1.22190845 | 4.215199903 | increase |
| Prevalence/100000/confirmed cases from beginning of pandemic | 489.000653 | 626.236726 | 677.8594761 | 688.970966 | increase |
| Prevalence/100000/active cases
from beginning of pandemic |
103.428018 | 72.13294456 | 17.65427161 | 5.102812645 | decrease |
| Prevalence/100000/discharged cases from beginning of pandemic | 382.8627263 | 550.4226862 | 655.3022008 | 674.7499497 | increase |
| Prevalence/100000/death cases
from beginning of pandemic |
2.709909 | 3.681095 | 4.903004 | 9.118204 | increase |
| Mortality Rate/1000-Total from beginning of pandemic | 0.027099 | 0.036811 | 0.04903 | 0.091182 | increase |
| Mortality Rate/1000-13days | 0.009414075 | 0.009711867 | 0.012219084 | 0.042151999 | increase |
Table 11- Average of confirmed new cases/new active cases/new cured cases/new death
| Period | Average Confirmed New Cases | Average New Active Cases | Average New Cured/Discharged | Average New Death |
| First 13 days before lockdown | 12845.23077 | 3947.153846 | 8822.692308 | 75.38461538 |
| First 13 day of lockdown | 10989.38462 | -2506 | 13417.61538 | 77.76923077 |
| Second 13 day of lockdown | 4133.769231 | -4362.461538 | 8398.384615 | 97.84615385 |
| First 13 day after
lockdown |
889.7692308 | -1005.076923 | 1557.307692 | 337.5384615 |
The average calculation shows that majority of these coronavirus new cases/new active cases/new discharged cases, was reported during the period 13 days before lockdown whereas average maximum new death were reported during 13 day period after lockdown(Table 11).
Regarding the impact of lockdown on the prevalence and mortality of the COVID-19 outbreak in Bihar, India, I found that 13 days after the lockdown there was no decline in the mean prevalence and the mean number
of daily deaths due to COVID-19 compared to 13 days before and 13 days during the lockdown (Tables 10) . However, the growth rate in the number of new daily cases of COVID-19 per 13 day (table9) and growth rate in the
number of new deaths per13 day attributed to COVID-19 each showed a positive but falling trend 13 days
after the lockdown period in Bihar, India. This data show a negative growth factor per 13 day during the 13 days following the lockdown for new daily cases and for new deaths per day. The change in growth rates
and growth rates per 13 day are expressed as: pre-lockdown vs. lockdown and after lockdown periods. Post-lockdown time periods, there was a declining rate of change per day for most except average new death. Regarding the mean prevalence of COVID-19 cases 13 days before, 26 days during and 13 days after lockdown, I found that the mean numbers of cases increased and there was no important impact of lockdown on the prevalence of COVID-19 cases (Tables 10). I calculated growth rate for new cases of COVID-19. The mean growth rate for number of new cases on a 13day basis was 0.21294272 and for new mortality rate was 0.06779661(table 9). It was found that, 13 days after the lockdown, the growth factor of the number of new daily cases decreased and the growth factor of new daily deaths was increased after the lockdown period (table 9). There is continuous decrease in Incidence/100000/ confirmed new cases, Incidence /100000/ confirmed new active cases, Incidence /100000/ new discharged cases, Prevalence/100000/active cases from beginning of pandemic during the period of observation while the other parameters have shown an increase during the observation periods (see table 9).
Discussion edit
The COVID-19 pandemic is a major public health problem which has infected millions of people worldwide. The idea of lockdown is associated with the incubation period of COVID-19, which is from 1-14 days (3). The lockdown methods have been implemented in many countries to control the spread of COVID-19 when other measures fail to achieve desired effect. For keeping an epidemic under control we must first control the rate of growth per day to become negative. In this study, I observed the impact of lockdown 13 days before(for comparison), two period of 13 days during and 13 days after(for comparison) lockdown on the epidemiological basis in the growth factor, incidence, prevalence and mortality because of the outbreak of novel coronavirus SARS-COV-2 in Bihar, India. I observed that 13 days after the Bihar lockdown there was no significant decline in the mean prevalence and mean mortality rate due to COVID-19 compared to 13 days before and 13-13(two observation) days during the lockdown in Bihar, India. However, daily cases of COVID-19 and growth rates showed declining trends by the end
of the lockdown and after the lockdown period, leading to a critically important negative growth rate by end of the lockdown period for both new daily cases. This negative growth rate per day shows that from a public health perspective, the lockdown had a positive effect on the pandemic. However, the growth rate never fell immediately following the lockdown and moreover lockdown cannot be enforced for a longer time due to economic and various other reasons of public concern, so the lockdown is not the only way to control the pandemic. However when all measures fail the government is forced to impose new lockdowns and encourage residents to isolate themselves in their houses for saving lives.
Through this article I recommend that along with other public health measures, lockdown should be enforced at
an early stage to prevent the COVID-19 infection from spreading to a large section of population causing increased morbidity and mortality as well as overburden on the health system. The study also demonstrates evidence that
lockdown measures are consistently beneficial. My study observation showed that the lockdown was beneficial in decreasing the rate of growth. The concept of a lockdown is theoretically very attractive because it minimizes the number of people exposed to contagious patients and therefore fewer people will be susceptible to getting infected but practically in poor states like Bihar it’s like a tragedy for people who are not able to afford food if they are not getting works on daily basis.
A lockdown may play a significant role when vaccination or prophylactic treatment is not available, as seen in
the case with COVID-19 pandemic. In this research, I observed and analysed the impact of 13 days before 26 days during and 13 days after lockdown on the prevalence and other epidemiology of COVID-19 cases in Bihar, India. My study findings support hypothesis that lockdown will significantly decrease the number of cases.
I have done this study in a different way and new people in public health may have little problem in understanding my observations. In many countries especially the developing countries long-term lockdown is not sustainable and practically possible as it has various mental, social, psychological and economic impacts. Future lockdown strategy should think of optimizing behavior, health promotion such as social distancing and mask wearing associated with social and cultural factors that can help in controlling the COVID-19 pandemic, because lockdown alone will not be effective if people will not adhere to this policy.
Study strength and limitation edit
This is the first article in the literature, to my knowledge, that have investigated the impact of a lockdown on
epidemiological trends of prevalence and mortality of the COVID-19 pandemic in Bihar, India. During the COVID-19 pandemic, to date, several mathematical modelling-based reviews/articles have been published to hypothesize the impact of a lockdown on the prevalence of COVID-19 cases. This is the first study, which analysed the impact of 13 days before, 13-13 days during and 13 days after lockdown on the prevalence trends of COVID-19 in Bihar especially point prevalence.
One of the peculiar strength is that the study data were gathered using reliable accredited sources including Government Health Department. I have analysed the growth factor and the growth rate per 13 day, which are
exceptional and totally new my idea to determine the epidemiological trends of a pandemic. A limitation is that I am unable to investigate confounding factors and bias such as how much people varies in: (1) adherence to lockdown, (2) adoption of protocols and guidelines of social distancing, (3) practice of health hygienic guidelines and (4) experience disease testing systems of nearest health centres.
Conclusion edit
My research shows that 13 days after lockdown there was no significant decline in the mean prevalence and mean mortality rate due to novel coronavirus SARS-COV 2 compared to 13 days before and 13-13 days during the lockdown in Bihar, India. The study found that daily cases of SARS-COV-2 patients, and the growth factor results declined and the growth rate per day both declined to an impressive negative level in the case of the growth rate. The Bihar model of lockdown is of significance in reducing the daily new cases as well as it was found that, 13 days after the lockdown, the growth factor of the number of new daily cases decreased and the growth factor of new daily deaths was increased after the lockdown period (table 9).
These findings may be useful for policy-makers who are thinking of further lockdowns to control the spread of the COVID-19 pandemic. Future lockdown policies should better work for optimizing health behaviour like social distancing and mask wearing associated with cultural factors that can halt spreading the COVID-19 pandemic, because lockdown will not be effective if people will not adhere to this policy, guidelines and protocols added with negative impacts of lockdown on livelihood in poor states like Bihar.
Declarations edit
-This paper has not been previously published and is not currently under consideration by another journal. The document is Microsoft word with English (United States) language & 8823 words Total.
- Ethics approval and consent to participate: Not applicable. This study has not involved any human or animals in real or for experiments. The data on the prevalence and mortality due to COVID-19 pandemic were taken from the Health Department, Bihar and other organizations which are also available online, hence ethical approval was not required.
-Consent for publication: Not applicable
-Availability of data and materials: The data & materials for study are mentioned in article and available as reference.
-Conflicts of Interest/ Competing Interest: There are no conflicts / competing of interest
- Funding-Self sponsored. No aid taken from individual or agency etc.
- Authors' contributions: The whole work is solely done by the Author - Dr Piyush Kumar, M.B.B.S. - Sri Krishna Medical College, EMOC- General Medical Officer- Bihar Health Services- Government of Bihar, India.
- Acknowledgements- I am thankful to Advocate Anupama my wife and daughters Aathmika and Atheeva for cooperation.
- Author information: The author is currently working as general medical officer for the government of Bihar.
-Financial Support & sponsorship: Nil
Author contact information
1 Department of Health, Government of Bihar, MOBILE - +919955301119/+917677833752,
Email drpiyush003@gmail.com
The article preprint is also submitted as preprint to various preprint server and preprint is having doi as well as searchable on various search engine. The article is not published in any peer reviewed journal.
Additional information edit
Acknowledgements edit
I am thankful to Advocate Anupama my wife and daughters Aathmika and Atheeva for cooperation.
Competing interests edit
There are no conflicts / competing of interest
Ethics statement edit
Not applicable. This study has not involved any human or animals in real or for experiments. The data on the prevalence and mortality due to COVID-19 pandemic were taken from the Health Department, Bihar and other organizations which are also available online, hence ethical approval was not required.
References edit
- ↑ "Bihar Population Sex Ratio in Bihar Literacy rate data 2011-2021". www.census2011.co.in. Retrieved 2021-12-27.
- ↑ Kumar, Dr Piyush (2021-12-27). What Impact Have SARS-CoV-2/Covid-19 Pandemic on the Reproductive and Child Health Programme of Bihar in India over the 3 months after nationwide Lock down announcement in March 2020? How SARS-CoV-2 Pandemic era does influence RCH Programme? Immunisation? Maternal Health? Family Planning?. doi:10.21203/rs.3.rs-348841/v4. https://www.researchsquare.com/article/rs-348841/v4.
- ↑ Kumar; Piyush, Dr (2021-04-25). What Are the Factors Responsible for Increase in SARS-CoV-2/COVID-19 Pandemic Related Cases and Death in India in 2021? How Does Environmental, Host & Agent Factors of Epidemiological Triad Do Influence & Can Be Utilised to Manage Ongoing Pandemic Cases and Deaths? (in en). Rochester, NY. doi:10.2139/ssrn.3833788. https://papers.ssrn.com/abstract=3833788.
- ↑ "COVID Live - Coronavirus Statistics - Worldometer". www.worldometers.info. Retrieved 2021-12-27.
- ↑ "Government of Bihar". state.bihar.gov.in. Retrieved 2021-12-27.
- ↑ Verma, Bhupendra Kumar; Verma, Mamta; Verma, Vikash Kumar; Abdullah, Rifah B.; Nath, Dilip C.; Khan, Hafiz T. A.; Verma, Anita; Vishwakarma, Ramesh K. et al. (2020-12). "Global lockdown: An effective safeguard in responding to the threat of COVID‐19". Journal of Evaluation in Clinical Practice 26 (6): 1592–1598. doi:10.1111/jep.13483. ISSN 1356-1294. PMID 32970386. PMC 7719340. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7719340/.
- ↑ Kumar, Piyush (2021-06-04). "Vaccination drive could be affected by frequent change in vaccines, guidelines, policies, interdisciplinary conflicts of medical sciences, mistrust, evil propaganda over Government data, lack of communication & health promotion in rural areas of India". dx.doi.org. Retrieved 2021-12-27.