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Update Report on Progress of Covid -19 Pandemic from 19th-25th January, 2022 Across Different Countries of the World

Research Article | DOI: https://doi.org/10.31579/2768-0487/101

Update Report on Progress of Covid -19 Pandemic from 19th-25th January, 2022 Across Different Countries of the World

  • Joseph Oyepata Simeon 1*
  • Joseph Opeyemi Tosin 2
  • Sabastine Aliyu Zubairu 3

1 Departmennt of Pharmacology and Toxicology, Faculty of Pharmaceutical Sciences, Federal University, Oye–Ekiti, Ekiti State, Nigeria.

2 Department of Pharmacy, University College Hospital, Ibadan, Oyo State, Nigeria.

3 Department of Pharmacology and Therapeutics, Faculty of Pharmacy, Gombe State University, Gombe State, Nigeria.

*Corresponding Author: Joseph Oyepata Simeon, Department of Pharmacology and Toxicology, Faculty of Pharmaceutical Sciences, Federal University, Oye–Ekiti, Ekiti State, Nigeria.

Citation: Joseph O. Simeon., Joseph O. Tosin., Sabastine A. Zubairu., (2023), Update Report on Progress of Covid -19 Pandemic from 19th-25th January, 2022 Across Different Countries of the World, Journal of Clinical and Laboratory Research. 6(2); DOI:10.31579/2768-0487/101

Copyright: © 2023, Joseph Oyepata Simeon. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Received: 27 April 2023 | Accepted: 12 May 2023 | Published: 19 May 2023

Keywords: Africa; America; continent; covid-19; Europe; Nigeria; USA

Abstract

Background: COVID-19 has set the globe on a difficult path. While several successes have been achieved, there are still many yet to be understood. This study provides an updated report on the progress of Covid -19 pandemic from 19th-25th January, 2022 across different countries of the world updated.

Material And Method: Data from one hundred and ninety-six (196) countries and regions of the world were gotten from United Nations Geo scheme. Results were collected and subsequently compared to the values obtained for the USA.

Result: Comparing available data with that of the USA, American continent had higher mortality comparism factor than infection cases, while European continents had higher infectious comparism value than mortality value. African continents, with exception of South Africa and Botswana, seems unbothered in value of mortality and infectivity. 

Conclusion: The new wave and virus variant have caused a renewed surge in its global consequence. There is the need to understand how Africa has survive all variant of the virus with minimal medical facilities.

Introduction

Scientists are still puzzled by the outbreak. Some believed that the virus began in animals while others think it’s from Wuhan lab. At some point, one or more humans acquired an infection from an animal or laboratory leakage to affect humans, and those infected humans may have transmitted the original or mutated viral version to other humans [1–4]. It can also be transmitted through contact with hands or surfaces that have been previously exposed by the virus and touch the body opening with the contaminated hands s [5–8]. Coronaviruses (CoV) is among the family of viruses that cause illness ranging from less severe to more severe diseases. CoV is a new variant that has not been previously identified in humans [9–15]. The new virus was subsequently named the “COVID-19 virus. The novel virus was first identified in Wuhan, a city in China, in December of 2019 [16–19]; an immediate lockdown in Wuhan and other surrounding cities failed to contain the outbreak, resulting its spread to different parts of the word [16–19]. On 30 January 2020, the World Health Organization (WHO) declared an international Public Health Emergency on the pandemic s [20–24]. Different strain of the virus has been discovered, the most notable of which are the delta and the Omicron variants (19-21). COVID-19 symptoms range from 

simple to life-threatening. Studies have shown that older persons are more likely to suffer from complications of the virus [24–29]. There is serious concern and study on the different waves caused by the pandemic. This may be due to weather conditions and predictable mutation [30–35]. There is a need to study these cases per country and region with respect to the infectious and spreading ability of the various variants. Different work has been done on the demographics, nature and strength of the virus, and analyzing the periodic information per time was also predicated in managing the trend [36–40]. The aim of this study was to provide update report on progress of Covid -19 pandemic from 19th-25th January, 2022 across different countries of the world.

Material and Method:

Study Area: Data from December 07 to December 13, 2021 were obtained from United Nations Geo scheme and WHO (WHO 2021).

Methodology

One hundred and ninety-six (196) nations from different continents and regions of the world was selected for this study. Data used where obtained from 19th to 25th of January, 2022 from United Nations Geo scheme and WHO [41]. The Data obtained for these countries over 7 days per 100000 populations, were analyzed and compared directly with the values gotten for USA. USA was used as a Comparism Factor (CF) or Oyepata Factor (OF) because it is a country with one of the best health systems and also has the highest COVID-19 cases with a relatively large population in the world. 

S/NCountry,Cases in 7 days (A)Deaths in 7 days (B)PopulationCIL7DPMDIL7DPMD/13460E/48.76
OtherDEFG
1USA4,496,82216,289334,077,7031346048.761.001.00
2France2,563,2511,85165,502,3663913228.262.910.58
3India2,183,8753,9281,401,494,92215582.800.120.06
4Brazil1,118,5212,323214,953,059520410.810.390.22
5Germany816,0691,08984,208,414969112.930.720.27
6Italy1,140,7832,45660,320,9451891240.721.410.84
7Russia375,5974,770146,033,616257232.660.190.67
8UK677,9211,85468,450,986990427.090.740.56
9Spain876,7921,09946,783,4741874123.491.390.48
10Turkey498,7361,22285,776,474581414.250.430.29
11Netherlands365,7636117,194,945212723.551.580.07
12Japan313,63989125,862,91524920.710.190.01
13Israel501,8681169,326,0005381412.444.000.26
14Argentina723,2151,28345,852,7071577327.981.170.57
15Portugal361,62028110,149,5963562927.692.650.57
16Poland241,2241,41037,780,927638537.320.470.77
17Belgium346,69217411,669,5372970914.912.210.31
18Australia413,85844925,968,4731593717.291.180.35
19Denmark272,8111165,824,5204683819.923.480.41
20Mexico300,3521,832131,078,326229113.980.170.29
21Czechia169,67515010,740,4611579813.971.170.29
22Peru352,53294233,699,1751046127.950.780.57
23Austria174,606779,087,812192138.471.430.17
24Switzerland243,850978,754,8872785311.082.070.23
25Sweden273,42717810,199,0302680917.451.990.36
26Romania120,59029519,034,321633515.500.470.32
27Ukraine121,40089443,317,391280320.640.210.42
28Chile108,23111619,376,13355865.990.410.12
29Iran39,71016185,695,4944631.880.030.04
30Norway126,776275,488,393230994.921.720.10
31Greece126,86765510,342,3741226763.330.911.30
32Georgia68,2902623,977,0331717165.881.281.35
33Colombia183,9931,46951,741,894355628.390.260.58
34Serbia112,6492168,681,6001297624.880.960.51
35S. Korea49,87721051,339,0999724.090.070.08
36Hungary96,0184179,621,480998043.340.740.89
37Philippines188,837636111,890,76116885.680.130.12
38Canada140,6781,14138,266,342367629.820.270.61
39Vietnam110,1861,03898,725,892111610.510.080.22
40Slovenia77,824832,079,3913742639.922.780.82
41Bangladesh83,20392167,288,2524970.550.040.01
42Slovakia44,9373005,463,832822454.910.611.13
43Jordan53,1588810,363,57351298.490.380.17
44Indonesia20,40064278,104,745730.230.010.00
45Lithuania43,015992,662,0931615837.191.200.76
46Kazakhstan95,5676619,132,41049953.450.370.07
47Uruguay78,333863,492,8042242724.621.670.50
48Bulgaria61,8915316,865,554901577.340.671.59
49Croatia60,9822904,065,1481500171.341.111.46
50Thailand53,54610170,077,4927641.440.060.03
51Latvia36,531721,853,1501971338.851.460.80
52Lebanon40,2731016,777,009594314.900.440.31
53Tunisia62,09218412,014,494516815.310.380.31
54Iraq42,4204741,650,82910181.130.080.02
55Pakistan47,63193227,681,4842090.410.020.01
56Panama67,536834,422,3101527218.771.130.38
57Réunion46,91438905,4345181441.973.850.86
58Bahrain24,59911,795,081137040.561.020.01
59Kuwait33,06994,370,57775662.060.560.04
60Estonia30,107261,327,9492267219.581.680.40
61Paraguay38,4571887,271,292528925.860.390.53
62Ecuador52,76312518,067,25629206.920.220.14
63Costa Rica35,732675,167,802691412.960.510.27
64Palestine14,610415,289,06627627.750.210.16
65Finland57,026915,554,3581026716.380.760.34
66Singapore22,14675,923,22937391.180.280.02
67Malaysia26,29110033,022,7197963.030.060.06
68Bolivia57,19138011,925,171479631.870.360.65
69Ireland38,081525,025,145757810.350.560.21
70Nepal59,6654329,966,41219911.430.150.03
71Saudi Arabia34,9251435,672,3229790.390.070.01
72Morocco47,93918937,603,44612755.030.090.10
73Moldova23,9461044,019,106595825.880.440.53
74Azerbaijan9,9419110,283,9409678.850.070.18
75Libya11,881877,019,256169312.390.130.25
76South Africa21,31084660,492,91435213.990.030.29
77Guatemala17,1039418,440,1809275.100.070.10
78Maldives16,1826555,6162912410.802.160.22
79Cuba22,5342811,315,66119912.470.150.05
80Cyprus11,032241,221,282903319.650.670.40
81Armenia5,586102,972,01918803.360.140.07
82UAE19,8032610,079,65519652.580.150.05
83Oman11,31185,312,10021291.510.160.03
84Belarus12,1091099,444,398128211.540.100.24
85Luxembourg15,6895642,102244347.791.820.16
86Venezuela14,3942728,308,2655080.950.040.02
87Egypt10,947226105,389,6711042.140.010.04
88Mongolia18,97893,361,87656452.680.420.05
89Bosnia and Herzegovina15,6462483,248,480481676.340.361.57
90Dominican Republic33,8702211,020,21630732.000.230.04
91Algeria13,8478145,104,5533071.800.020.04
92Qatar21,58872,807,80576892.490.570.05
93North Macedonia11,6651272,083,238559960.960.421.25
94Guadeloupe20,8069400,2325198522.493.860.46
95Martinique11,62013374,8043100334.682.300.71
96Iceland10,1511344,751294442.902.190.06
97Albania14,529402,872,818505713.920.380.29
98Sri Lanka5,9479921,555,4992764.590.020.09
99Uzbekistan9,1292334,237,2802670.670.020.01
100Botswana6,017312,426,780247912.770.180.26
101Montenegro8,34145628,1921327871.630.991.47
102New Caledonia2,4691289,84585183.450.630.07
103El Salvador4,768256,538,0567293.820.050.08
104Faeroe Islands4,465249,1579083140.696.750.83
105Trinidad and Tobago5,3841111,406,668382778.910.281.62
106Barbados4,2466287,9331474620.841.100.43
107Belize5,14811409,0551258526.890.940.55
108Laos4,787297,442,7356433.900.050.08
109Afghanistan1,2881340,315,711320.320.000.01
110Jamaica6,450582,981,645216319.450.160.40
111Zambia4,5373219,198,3412361.670.020.03
112Channel Islands2,3845176,4011351528.341.000.58
113Suriname5,65526594,958950543.700.710.90
114Seychelles1,521399,3121531530.211.140.62
115Cameroon4,4471427,591,3381610.510.010.01
116Ethiopia3,56196119,469,104300.800.000.02
117Sudan3,4882145,469,298770.460.010.01
118Guyana4,59447792,565579659.300.431.22
119Kyrgyzstan4,944186,694,6137392.690.050.06
120Cayman Islands0066,94400.000.000.00
121Myanmar975554,987,647180.090.000.00
122Madagascar1,5485428,817,252541.870.000.04
123Malta2,01727443,406454960.890.341.25
124Honduras5,0203210,154,0244943.150.040.06
125French Guiana4,08011310,9301312235.380.970.73
126Andorra4,813377,4616213438.734.620.79
127Bhutan7810785,0659950.000.070.00
128Solomon Islands6192713,5358682.800.060.06
129Uganda1,7786048,025,301371.250.000.03
130San Marino1,147534,04433692146.872.503.01
131Zimbabwe1,8895015,205,5261243.290.010.07
132Mozambique2,6512532,640,542810.770.010.02
2ws1Palau590018,231323620.002.400.00
134Saint Lucia2,30112184,9571244164.880.921.33
135Gibraltar1,053033,675312690.002.320.00
136Kenya2,3355855,645,701421.040.000.02
137Curaçao1,95614165,1561184384.770.881.74
138New Zealand51705,002,1001030.000.010.00
139Mauritius55201,275,1124330.000.030.00
140Liechtenstein831038,301216970.001.610.00
141Ghana1,8932932,099,491590.900.000.02
142Grenada1,4781113,349130398.820.970.18
143Hong Kong45307,593,331600.000.000.00
144Greenland1,238156,9262174817.571.620.36
145Fiji1,91933906,736211636.390.160.75
146Haiti742311,622,670640.260.000.01
147Gabon79312,308,8353430.430.030.01
148Monaco847039,683213440.001.590.00
149Nigeria1,33717214,223,24660.080.000.00
150Dominica770372,2691065541.510.790.85
151Mauritania1,790234,843,0043704.750.030.10
152Angola3,3192134,483,018960.610.010.01
153DRC1,776093,867,492190.000.000.00
154Antigua and Barbuda677199,213682410.080.510.21
155Senegal1,2792117,441,958731.200.010.02
156Papua New Guinea12419,215,300130.110.000.00
157Aruba1,1867107,4841103465.130.821.34
158Malawi1,0385419,911,995522.710.000.06
159Rwanda2,2452013,460,2071671.490.010.03
160Isle of Man682085,74679540.000.590.00
161Kiribati420122,3513430.000.030.00
162Bermuda1,118461,9131805864.611.341.32
163Namibia764912,613,74929234.820.020.71
164Caribbean Netherlands854126,6093209437.582.380.77
165French Polynesia5190283,48118310.000.140.00
166Taiwan460023,885,078190.000.000.00
167China44701,448,129,94000.000.000.00
168Ivory Coast9281927,411,758340.690.000.01
169Syria2912118,173,320161.160.000.02
170Mayotte1,0631283,23037533.530.280.07
171Burundi388012,450,875310.000.000.00
172Bahamas1,13312399,196283830.060.210.62
173Brunei1910444,1144300.000.030.00
174Tanzania1,5253362,425,392240.530.000.01
175Cambodia247017,085,369140.000.000.00
176Saint Pierre Miquelon24205,749420940.003.130.00
177Turks and Caicos375439,5469483101.150.702.07
178Eritrea30563,624,146841.660.010.03
179Lesotho23322,169,1511070.920.010.02
180St. Barth35509,925357680.002.660.00
181Saint Kitts and Nevis277453,795514974.360.381.52
182Benin273112,625,546220.080.000.00
183Togo31648,585,747370.470.000.01
184Burkina Faso224021,809,963100.000.000.00
185Guinea-Bissau34412,041,6011680.490.010.01
186Djibouti28301,010,7512800.000.020.00
187Tajikistan13409,876,647140.000.000.00
188Equatorial Guinea24031,475,8661632.030.010.04
189Chad186517,171,372110.290.000.01
190Liberia12225,245,781230.380.000.01
191St. Vincent Grenadines584111,49852035.880.040.74
192Comoros430898,918480.000.000.00
193Sierra Leone4908,233,73560.000.000.00
194Somalia1,127016,594,596680.000.010.00

Table 1: The cases and death of COVID-19

Statistical Analysis

In this work markers as cumulative cases and cumulative cases of death per 1,000,000 population were analyzed against that of the USA. Bivariate analysis and Chi-square test was used to compare the proportions of all variables. Country observations are scaled to represent a comparison of two countries similar in all other respects. 

Results

Comparing available data with that of the USA, American continent had higher mortality comparism factor than infection cases, while European continents had a higher infectious comparism value than mortality value. African continents, with exception of South Africa and Botswana, have an unbothered value of mortality and infectivity when compared to the rest of the world (Table 1). 

Values of CF1 (or OF1) and CF2 (or OF2) represent case/incidence and mortality index.

Factor of more than 1 = very high infection and mortality index

Factor of approximately 1 = high infection and mortality index

Factor of ≤1 but ≥0.5 = moderately high infection and mortality index

Factor of ≤ 0.5 but ≥ 0.1 = low infection and mortality index

Factor of <0>

Key:           

CIL7DPM = Cases in the last 7 days/1M population

DIL7DPM = death in the last 7 days/1M population

Data used were obtained from WHO/World meter’s as at 18th, January, 2022

CF = Comparism Factor

OF= Oyepata Factor

Fig. 1 and 2 obtained for USA were used in determining the comparism factor (CF) or Oyepata Factor which is a ratio of figure obtained to that of a particular country population divided by that of the USA.

Figure 1: graph showing Comparism factor per country relative to USA19th to 25th of January 18, 2022.

Figure 2: graph showing death Oyepata factor caused by Covid-19 for each country relative to USA as at 19th to 25th, January, 2022. X-axis represent Comparism (Oyepata) factor, Y-axis represent countries

Discussion

From analyzed data, American continent had higher mortality comparism factor to infection cases, while European continents had higher infectious comparism value than mortality value. African continents, with exception of South Africa and Botswana, has an unbothered value of mortality and infectivity when compared to the rest of the world. Recently, there has been new mutated strain of the virus from the original strain, with many possible strains unfortunately expected to keep reshaping our understanding of the situation [42–46]. This has caused unprecedented burden to public health, food and world workforce. Various variant has been identified in several countries, and it could potentially affect thousands to millions of deaths if not properly handled [47–49]. Africa is known to be an acceptable home to several infectious diseases such as dengue fever, small pox, measles chicken pox, Ebola, and polio disease [50–53]. In many cases, vaccination has been 

developed against some of this infection or the body immune system has successfully found a way to defend against this pathogen [54–58]. This may have had a beneficial effect against exposure to same or related organism. There is the likelihood of the virus spreading fast across African populations within a minimal period of time causing a large proportion to have been exposed to the virus without manifesting obvious symptoms and may have even recovered. America continent appears to have more infectivity and higher reports of mortality from the new variant of Covid-19. Africa has been least plagued by the all variant at all phases. Also, most European countries have lesser mortality ratio when compared to American continents. These observations interesting compared previous works on the cumulative effect of the virus [59–65]. Africans appear to be unaffected from this seemly uncontrollable and lethal unleash. Apart from fewer cases of the infection, Africans have shown potential to have much lesser mortality even when compared to case of the infection [65–66]. This suggested that Africans body system have over time developed a more progressive, robust and faster immune response that reduces chances of the virus causing disease related health complication. Compared to previous cumulative observation, though mortality rate remained higher than other western countries, USA has made remarkable stride in preventing and reducing the cases of infection compared to several other countries that suffered same fate from the virus. From available data, Africa which generally is classified as third world or clearly underdeveloped do not have severe medical consequences of the infection, and when infected they tends to recover faster with lower chance of complications and mortality. As previously noted, African slives as a community and in dense clusters which is obviously different to most western countries that exist in solitary system [67,67]. Thus, it is expected that most individuals in Africa may have been exposed to the virus without knowing or developing major symptoms. This has made several observers around the world to speculate that Africa may consequentially become a graveyard. Reasons for this fortunately unexpected result has puzzled many analysts around the world. Studies have shown, that because of poor health and environment, the immune systems of African children tend to develop faster and more robust compared to Dutch children [69]. Childhood Exposure to pathogenic organism may have boasted the immune system and protect children from developing certain allergies and other infectious diseases, on later exposure to the similar allergen or pathogen [70]. This view is also supported with data and comparism factor obtained from Haiti. Haiti is currently the poorest country in the Latin America and Caribbean region and among least developed countries in the world [71–72]. They have one the least case of infection and mortality resulting in little to no significant value of comparism factor. Thus, childhood or early exposure to some diseases in poor countries may have encouraged a more robust immune response to same or related infection. Therefore, several African countries be both vulnerable and potentially more defensive against the coronavirus.

Conclusion

Many underdeveloped countries, particularly Africans and Haiti, have developed an unexpected survival mechanism. While there appears to be a conflicting approach on how best to manage and live with the virus, the virus and its apparently unending variants suggests that understanding and utilizing Africans biological survival mechanism may be the best way to regain near normal freedom.

Significance of the Study

The study discovered that America and Europe, two of the most developed continents in the world are ironically still the most affected by the pandemic. Africa, against public expectation has shown little sign of been affected by the pandemic. This may be due to environmental exposure or vaccination against related microorganism, which may have resulted to some kind of biological immunity that became beneficial against subsequent exposure. The study also revealed that Africa, like every other continent need vaccine but not on a relatively desperate demand.

Authors’ contributions

Joseph OS and Joseph OT were involved in the collection of data and development of model for analysis. Joseph OS, Joseph SO, Joseph OT and Sebastine AZ were responsible for analysis and writing of this manuscript.

Conflict of Interest

The authors declare that there are not any potential conflicts of interest.

Acknowledgement

The authors wish to thank everyone who has contributed to the collation and analysis of data. Special recognition to United Nations Geo scheme and WHO granting access to information.

References

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