Mitigating the Effects of COVID-19 through Vaccination: Evaluating Leading Countries across Continents of the World

Abstract

This research investigates COVID-19 vaccine efficacy across six countries: India, South Africa, France, Australia, the USA, and Brazil, examining their impact on reducing deaths and containing the virus. It analyzes vital epidemiological metrics during pre-vaccination and post-vaccination periods until February 5, 2023. The countries are grouped by their Aridity Index, reflecting climate variations. Employing Pearson correlation, the study explores the relationship between the Aridity Index and vaccination period rates, noting some moderate associations but lacking statistical significance at a 5% level. Comparing case fatality and infection rates before and during vaccination showed no significant differences. However, incidence rates displayed a notable discrepancy at the 5% significance level. The study underscores the need for non-pharmaceutical measures alongside vaccination efforts to mitigate the increase in incidence and infection rates. It emphasizes that while COVID-19 vaccinations play a crucial role, complementary measures remain essential in effectively managing the pandemic. Overall, this research offers critical insights into vaccine efficacy across diverse countries, advocating a continued multi-faceted approach to combat the global health crisis.

1. Introduction

The first coronavirus 2019 (COVID-19) outbreak surfaced in December 2019 in Wuhan, China [1, 2]. The disease rapidly spread across every continent except Antarctica, claiming the lives of thousands of people as it extended its reach globally [3]. The effects of the COVID-19 pandemic were first observed in China, Europe, and North America, followed by subsequent effects in South America, Africa, and the Western Pacific [4]. The majority of recorded cases were linked to the local Huanan South China seafood market, which traded in wild animals [5]. The virus is capable of spreading through close contact and respiratory droplets, which are released when an infected person coughs, sneezes, or exhales. Inhalation of these aerosols can lead to the virus entering the respiratory system of individuals, facilitating its transmission from person to person [6]. To combat the COVID-19 epidemic, countries implemented various preventive measures, including lockdowns, social distancing, mask mandates, and emphasizing personal hygiene practices like regular handwashing and avoiding touching the face [7]. Vaccines have been extensively considered as an element of an exit strategy to allow a return to prior working, educational, and socializing patterns [8]. Over fifty (50) companies initiated intensive scientific research in early 2020 to develop COVID-19 vaccines [9]. The collective efforts resulted in the successful development of various COVID-19 vaccines, such as Johnson & Johnson’s Janssen, Pfizer-BioNTech, Moderna, Oxford-AstraZeneca, and several others [10].

The COVID-19 pandemic rapidly spread to Europe in January 2020, with France reporting the first case of travel-related infection from China. Italy later faced a significant increase in cases in February, and by March 2020, COVID-19 had affected all European Member States [11]. European Union/European Economic Area countries implemented a range of measures, including pharmaceutical and non-pharmaceutical approaches, to curb the spread of the virus and mitigate the impact of the pandemic [12]. In Europe, the country with the highest number of infected cases is France. On January 24, 2020, the first COVID-19 case in France was officially confirmed [13]. France initiated its COVID-19 vaccination campaign in January 2021, initially targeting high-risk individuals. Subsequently, in the spring of 2021, the campaign expanded to include the rest of the French population [14]. The first COVID-19 case in South America was reported on March 26 [15]. COVID-19 negatively affects the population health of South American (S.A.) countries since they have fragile public health systems [16].To catch up with the goal of immunizing at least 60–70% of the population, South American countries strive to create opportunities for vaccine diplomacy as the rate of COVID-19 immunization rapidly increases worldwide [17].Brazil has the highest number of infected cases in South America. Brazil received its first case report on February 25, 2020 [18].

The initial COVID-19 case in Africa was confirmed in Egypt in the middle of February 2020 [19]. The virus has rapidly spread over the continent, raising serious health concerns [20]. Among African countries, South Africa, Morocco, Tunisia, Ethiopia, and Libya are identified as the five high-burden nations, exhibiting case fatality rates (C.F.R.) estimated at approximately 0.15 percent, 0.04 percent, 0.2 percent, 0.00 percent, and 0.08 percent, respectively [21]. South Africa holds the highest number of COVID-19 cases among African countries, with the first reported cases documented on March 6, 2020. Australia’s initial response to the COVID-19 pandemic proved highly effective during its first year, resulting in low case incidence and case-fatality rates [22]. In June 2021, the Delta variant of SARS-CoV-2, a variant of concern, was first detected in New South Wales, the most populous state in Australia. From this single case, an outbreak ensued, spreading throughout the region [23].

The Republic of Singapore achieved the milestone of being the first Asian country to report a COVID-19 case on January 25, 2020 [24].COVID-19 extended to other regions of Asia, with infection rates very high in Turkey, India, Indonesia, and Iran [25]. Asian countries have actively undertaken various measures to develop COVID-19 vaccines, emphasizing their commitment to combating the pandemic [26]. India has emerged as the country with the highest number of COVID-19 cases in Asia. The initial case of the 2019 coronavirus disease (COVID-19) in India was officially recorded on January 27, 2020, in Kerala [27].In North America, the U.S.A. became the epicenter of coronavirus, experiencing the highest number of cases and fatalities. The first COVID-19 patient in the United States of America was recorded in Washington State on January 15, 2020 [28]. Climate and environment have a significant role in transmission as the COVID-19 epidemic spreads over the world over multiple seasons [29]. It should be noted that prior epidemiological and laboratory research have revealed that temperature is essential for the survival and transmission of coronaviruses. Seasonal fluctuations are also influenced by environmental factors such as humidity, rain, U.V. intensity, and wind speed [30].

According to the data available, incidence rates and mortality differ from one country to another and from one continent to another. Dietary practices, climate, social interactions, genetic variances, governmental frameworks, and use of chloroquine (C, Q.) and anti-tuberculosis (T.B.) vaccine may all contribute to the diversity (Bacillus Calmette–Guerin, B.C.G.) [31]. Asia, Africa, Europe, Oceania, North America, South America, and Antarctica are the seven continents globally. As of May 18, 2020, Antarctica remained the only continent without a confirmed case of COVID-19. While no published scientific evidence supports this exemption, researchers are actively studying the factors contributing to the apparent immunity in this region [32]. Six countries from six continents were selected as representatives based on their high number of COVID-19 cases: India for Asia, South Africa for Africa, France for Europe, Australia for Oceania, the U.S.A. for North America, and Brazil for South America. The worldwide healthcare system requires biomedical and clinical interventions to address COVID-19.

The effectiveness of COVID-19 vaccination varies across countries, regions, and continents, prompting the exploration of factors influencing behavior during the periods of no-vaccination and vaccination. In this light, this study aims to examine and compare the rates of chaos induced by COVID-19 during the period of non-pharmacological intervention (before vaccination) and at the commencement of pharmacological intervention (during vaccination) in six (6) distinct leading countries for COVID-19 in their respective continents.

2. Method

2.1 Data extraction

Data sets pertaining to daily new cases and death cases of COVID-19, along with variables such as population size and the number of people vaccinated, were examined for six (6) distinct leading countries for COVID-19 across their respective continents. These datasets were surveyed for two (2) periods and were obtained from the official website of “Our World in Data” (https://ourworldindata.org/coronavirus). Additionally, world annual averaged temperatures and precipitation data were sourced from the World Bank data catalog.

2.2 Analysis of data

The pre-vaccination period was defined as the time from the first recorded case until the commencement of vaccination in each country. In contrast, the during-vaccination period encompassed the period from the start of vaccination in each country until February 5, 2023. This study estimates case fatality rate (C.F.R.), infection rate (IRR), and incidence rate (I.R.) for the two periods of vaccination using eqs. (1)–(3).

The regression model approach obtained the case fatality rate (C.F.R.). The equation is written as

$$\text{death}\text{cases}\text{=}{\beta }_{\text{0}}\text{+}\left({\beta }_{\text{1}}\text{×confirmed}\text{cases}\right)\text{+}{\epsilon }_{\text{I}}$$E1

$$\text{IRR=}\frac{\text{number of people infected}}{\text{number of days of infection}}$$E2

$$\text{IR=}\frac{\text{x}}{\text{y}}$$E3

where x is the number of persons who develop the disease over time and y is the number of persons initially without the disease who were followed for the defined period.

The aridity index (A.I.) functions as a numerical gauge of the dryness level in the climate at a specific location, represented as I. As per the classification by De Martonne, I < 5 is categorized as Hyper-Arid; it falls under the Arid classification when 5 < I < 10, Semi-Arid when 10 < I < 20, Mediterranean when 20 < I < 24, Semi-Wet when 24 < I < 28, wet when 28 < I < 35, very wet when 35 < I < 55, and extremely wet when I > 55 [33, 34, 35]. The Index (I) is obtained as follows:

$$I=\frac{P}{T+10}$$E4

P represents the average annual precipitation (mm), T denotes the average yearly temperature (°C), and I is the De Martonne aridity coefficient.

3. Results

This study investigated the daily patterns of COVID-19 incidence, spread, and fatality rates in correlation with vaccine efficacy levels, both in the absence of vaccination and during vaccination. The analysis focused on the aggregation of risks associated with exposure to climatic conditions in six countries that recorded high COVID-19 cases in their respective continents.

3.1 Descriptive statistics and estimated cases

The descriptive statistics of daily confirmed and death cases related to COVID-19 in the analysis elucidate the sampling technique and data measures during two distinct periods. The sampling before vaccination encompassed the time from the day of the first reported COVID-19 case until the initiation of vaccination for each country under study. Concurrently, the sampling during vaccination extended from the commencement of vaccination in each country until February 5, 2023, as outlined in Table 1. Right before the total number of infected people with COVID-19 in India reached ten million, five hundred and forty-two thousand, eight hundred and forty-one (10,542,841) on 15th January 2021, the lowest and highest daily confirmed cases recorded were zero (0) and ninety-seven thousand, eight hundred and ninety-four (97,894) respectively, while the lowest and highest recorded death cases were zero(0) and two thousand and three (2003) respectively. The average within the pre-vaccination period is twenty-nine thousand, nine hundred and fifty-one (29,951) and four hundred and thirty-two (432) for confirmed and death cases, respectively. Within the vaccination period, thirty-four million, one hundred and forty-three thousand, seven hundred and seventy-six (34,143,776)cases were reported from among uninfected populations of one billion, four hundred and seventeen million, twenty-one thousand and twenty-six (1,417,021,026) that made it to the vaccination period in India. Between 16th January 2021 and 5th February 2021, the average daily reported confirmed and death cases were forty-five thousand, six hundred and forty-seven (45,647)and four hundred and ninety-five (495), respectively. Focusing on the realistic patterns of figures, the United States of America recorded a shock in the daily average confirmed cases of forty-nine thousand, eight hundred and fifty-one (49,851) and death cases of one thousand and forty-six (1046) during vaccination (Table 1).

Countries	Period	Total population	Sample	Confirmed/Death cases
				Min	Max	Mean	Std dev
India	Before	1,417,173,120	10,542,841	0/0	97,894/2003	29,951/432	29,066/383
	During	1,417,021,026	34,143,776	0/0	414,188/4529	45,647/495	85,309/938
South; Africa	Before	59,893,884	1,496,439	0/0	21,980/844	4276/139	4778/161
	During	59,845,406	2,541,676	0/0	37,875/633	3545/75	5280/114
France	Before	67,813,000	2,674,851	0/0	104,707/1438	7914/187	13,737/283
	During	67,749,855	37,364,037	0/0	502,507/1008	48,778/132	75,396/145
Australia	Before	26,177,410	28,926	0/0	716/59	74/2	128/6
	During	26,176,500	11,313,627	0/0	175,271/504	15,935/25	22,618/39
U.S.A.	Before	338,289,856	16,251,278	0/0	236,903/3333	49,851/1046	52,591/673
	During	337,988,614	86,150,275	1994/0	1,354,502/4408	109,886/1035	144,830/1008
Brazil	Before	215,313,504	8,480,783	0/0	87,969/1518	26,095/642	18,773/407
	During	215,104,062	28,281,672	0/0	287,149/4148	37,810/651	39,221/829

Table 1.

Descriptive statistics of the datasets.

During the period under consideration, in most of the countries studied, there is a higher count of confirmed and death cases observed during vaccination compared to the period before vaccination (Figures 1–2). Additionally, the duration of days considered during vaccination exceeds the duration before vaccination (Figure 3). From Table 2 and De Martonne’s global classification [33], India falls within the “Wet region,” South Africa and Australia within the “Semi-arid regions,” France, U.S.A., and Brazil within the “Very wet regions” (Table 2).

Figure 1.

The flow of COVID-19 daily cases in each country for the two periods (before and during vaccination).

Figure 2.

The flow of COVID-19 death cases in each country for the two periods (before and during vaccination).

Figure 3.

The number of days of COVID-19 cases in each country for the two periods (before and during vaccination).

Countries	Temp	Precipitation (mm)	De Martonne (I)
India	25.3	1197	33.9093
South Africa	17.4	495	18.0657
France	12.5	802	35.6444
Australia	21.8	534	16.7925
USA	11.7	763	35.1613
Brazil	24.3	1746	50.9038

Table 2.

Climate conditions of countries based on the aridity index.

The study revealed that, among 10,542,841 individuals diagnosed with COVID-19 within the specified time interval, the proportion of Indian people who died was 1.2% before vaccination (refer to Table 3). During the vaccination period, a sample of 34,143,776 people diagnosed with the disease showed a reduced fatality rate of 0.9%.

Countries	Case Fatality Rate		Infection Rate		Incidence Rate		Specific Mortality
	Before	During	Before	During	Before	During	Before	During
India	0.012; (R^2 = 0.950)	0.009; (R^2 = 0.645)	29951.2528	45464.4155	0.0074	0.0241	0.0001	0.0003
South Africa	0.026; (R^2 = 0.657)	0.014; (R^2 = 0.447)	4275.54	3539.9387	0.0250	0.0425	0.0008	0.0009
France	0.009; (R^2 = 0.181)	0.000; (R^2 = 0.065)	7890.4160	48461.7860	0.0394	0.5515	0.0009	0.0015
Australia	0.021; (R^2 = 0.309)	0.001; (R^2 = 0.340)	73.7908	15823.2546	0.0011	0.4322	0.000035	0.0007
USA	0.007; (R^2 = 0.293)	0.003; (R^2 = 0.249)	49850.5460	109885.5548	0.0480	0.2549	0.0009	0.0024
Brazil	0.018; (R^2 = 0.639)	0.012; (R^2 = 0.254)	26014.6718	37708.896	0.0394	0.1315	0.0010	0.0023

Table 3.

Behavioral expression of rates of COVID-19 infection with and without vaccines.

Before vaccination, India had an approximate infection rate of 29,951.2528. During vaccination, the infection rate increased to 45,464.42, with 34,143,776 individuals diagnosed with the disease.

However, the incidence rate, representing the number of new cases in India within the defined time interval before vaccination as a proportion of the one billion, four hundred and seventeen million, one hundred and twenty thousand (1,417,173,120) people at risk, was 0.0074 per one thousand people. This rate increased to 0.0241 per one thousand among 1,417,021,026 people at risk during vaccination.

In South Africa, categorized as a Semi-arid region according to De Martonne’s global classification (refer to Table 2), the study found that 2.6% of people among 1,496,439 diagnosed with COVID-19 died before vaccination (refer to Table 3). During the vaccination period, a sample of 2,541,676 people diagnosed with the disease showed a reduced fatality rate of 1.4%.

The infection rate, indicating the spread power within the population, was estimated to be 4275.54 before vaccination. During the vaccination period, this rate decreased to 3539.9387. The incidence rate, representing the proportion of new cases among 59,893,884 people at risk, was 0.0250 per one thousand people before vaccination. This rate increased to 0.0425 among 59,845,406 people in South Africa at risk during the vaccination period.

The study found that among 2,674,851 individuals diagnosed with COVID-19 within the defined time interval, the proportion of French people who died was 0.9% before vaccination (see Table 3). During the vaccination period, a sample of 37,364,037 people diagnosed with the disease showed a remarkable drop in the fatality rate to 0.0%, indicating a significant mitigating influence of the vaccine on the case fatality rate. However, the COVID-19 spread rate was estimated to be 7890.4160 within the 339 days of the period before vaccination, and this rate increased to 48,461.7860 during the 771 days of people receiving COVID-19 vaccines. Moreover, the incidence rate, considering 67,813,000 people in France at risk before vaccination, was 0.0394 per one thousand people. During the vaccination period, this rate increased to 0.5515 per one thousand people of the 67,749,855 in the population at risk, indicating a higher incidence compared to before vaccination.

The study found that among 28,926 individuals diagnosed with COVID-19 within the defined time interval, the proportion of Australian people who died was 2.1% before vaccination (refer to Table 3). During the vaccination period, a sample of 11,313,627 people diagnosed with the disease showed a reduced fatality rate of 0.1%, indicating a significant mitigating influence of the vaccine on the case fatality rate. However, within 392 days after Australia recorded its first case, the infection rate was 73.7908, and the spread rate during the vaccination period was 15,823.2546. This indicated no significant effect of the vaccines on the COVID-19 spread rate in Australia. The incidence rate before vaccination, considering 26,177,410 people at risk, was estimated at 0.0011 per one thousand. During vaccination, this rate increased among 26,176,500 people at risk to 0.4322 per one thousand, suggesting that COVID-19 vaccines show no efficacy on the incidence rate.

The study revealed that among 16,251,278 individuals diagnosed with COVID-19 within the defined time interval, the proportion of people in the United States who died was 0.7% before vaccination (see Table 3). During the vaccination period, a sample of 86,150,275 people diagnosed with the disease showed a reduced fatality rate of 0.3%, indicating a mitigating influence of the vaccine on the case fatality rate. Before vaccination, the case dispersed within 326 days, with an infection rate of 49,850.5460. With the spread increasing during the vaccination period, the estimated infection rate reached 109,885.5548. This suggests that COVID-19 vaccines show no efficacy on the behavioral spread of the infection. However, the incidence rate, considering 338,289,856 people in the United States at risk before vaccination, was 0.0480 per one thousand people. During the vaccination period, this rate increased among 337,988,614 people at risk to 0.2549 per one thousand, indicating that the incidence rate is higher than it was before vaccination.

The study found that among 8,480,783 individuals diagnosed with COVID-19 within the defined time interval, the proportion of people in Brazil who died was 1.8% before vaccination (see Table 3). During the vaccination period, a sample of 28,281,672 people diagnosed with the disease showed a reduced fatality rate of 1.2%, indicating a mitigating influence of the vaccine on the case fatality rate. Before vaccination, the case dispersed within 326 days, with an infection rate of 26,014.6718. With the spread increasing during the vaccination period, the estimated infection rate reached 37,708.896. This suggests that COVID-19 vaccines show no efficacy on the behavioral spread of the infection. However, the incidence rate, considering 215,313,504 people in Brazil at risk before vaccination, was 0.0394 per one thousand people. During the vaccination period, this rate increased among 215,104,062 people at risk to 0.1315 per one thousand, indicating that the incidence rate is higher than it was before vaccination (Figure 4).

Figure 4.

(a) The infection rate before and during the vaccination period for the six countries, (b) the incidence rate before and during the vaccination period for the six countries. (c) the case fatality rate before and during the vaccination period for the six countries.

3.2 Test of association

To evaluate the magnitude and direction of the relationship between the Aridity Index and Epidemiological Metrics used in this research, the Pearson product-moment correlation coefficient and the p-value were obtained in Table 4.

	Vaccination; Period	P-value	Pearson Correlation coefficient
Case Fatality Rate	Before	0.301	−0.51
	During	0.791	0.14
Infection Rate	Before	0.226	0.581
	During	0.35	0.468
Incidence rate	Before	0.205	0.604
	During	0.841	−0.106
Specific Mortality	Before	0.286	0.524
	During	0.16	0.653

Table 4.

Correlation analysis between aridity index and epidemiological metrics.

Table 5 presents the outcomes of the Pearson correlation analysis between the Aridity Index (a numerical gauge of climate dryness) and Case fatality, Infection, Incidence, and Specific mortality rates for the two vaccination periods. The correlation coefficient between the Aridity Index and Case Fatality Rate is −0.51. This indicates a moderate negative relationship between these variables before the vaccination period. The correlation coefficient between the Aridity Index and Case Fatality Rate is 0.14. This suggests a weak positive relationship between these variables during the vaccination period. The p-values associated with both correlations are 0.301 and 0.791, respectively. Both p-values are greater than 0.05, indicating that the observed correlations are not statistically significant at a 5% significance level. The correlation coefficient between the Aridity Index and Infection Rate is 0.581. This suggests a moderate positive relationship between these variables before the vaccination period. The correlation coefficient between the Aridity Index and Infection Rate is 0.468. This also indicates a moderate positive relationship between these variables during vaccination. The p-values associated with both correlations are 0.226 and 0.35, respectively. Both p-values are greater than 0.05, indicating that the observed correlations are not statistically significant.

Rates		Mean	Standard deviation	T-test
Infection rate	Before	19676.0362	19060.8687	0.437
	During	43480.6409	36964.4789
Incidence rate	Before	0.0267	0.0190	0.003
	During	0.2395	0.2152
Case Fatality rate	Before	0.0065	0.0060	0.505
	During	0.0155	0.0074

Table 5.

Comparison of rates before and during vaccination.

The correlation coefficient between the Aridity Index and the Incidence Rate is 0.604. This suggests a moderate positive correlation between these variables before the vaccination period. The correlation coefficient between the Aridity Index and Incidence Rate is −0.106. This suggests a weak negative relationship between these variables during the vaccination period. The p-values associated with both correlations are 0.205 and 0.841, respectively. Both p-values are greater than 0.05, indicating that the observed correlations are not statistically significant. The correlation coefficient between the Aridity Index and Specific Mortality is 0.524. This shows a moderate positive relationship between these variables before the vaccination period. The correlation coefficient between the Aridity Index and Specific Mortality is 0.653. This suggests a moderate positive relationship between these variables during the vaccination period. The p-values associated with both correlations are 0.286 and 0.16, respectively. Both p-values are greater than 0.05, indicating that the observed correlations are not statistically significant. Cases where there are no significant statistical association implies there is no linear relationship at the level of significant chosen. However, there may be a linear significant statistical association at other level of significant and other form of relationship other than linear may exist.

Overall, none of the observed correlations are statistically significant at 5% significance level.

3.3 Test of significant differences between the periods

The mean (standard deviation) of Infection, Incidence, and Case fatality rates before the vaccination period are 19676.0362 (19060.8687), 0.0267 (0.0190), 0.0065 (0.0060), while during vaccination, are 43480.6409 (36964.4789), 0.2395 (0.2152), 0.0155 (0.0074) respectively.

Vaccines have been developed to safeguard humans against COVID-19 and SARS-CoV-2 infection. To assess the efficacy of the vaccine in combating this severe disease, a comparison was made between periods when vaccination was not in use and when it was endorsed for use among citizens of the countries considered in this study. An independent t-test was performed, and the findings suggest that there is no statistically significant difference in the means of case fatality and infection rates before and during the vaccination period, with p-values of 0.505 and 0.437, respectively, at a 95% confidence level. However, there were significant differences in the means of incidence rates between the two periods at a 95% confidence level, with a p-value of 0.003.

4. Discussions

The effectiveness of COVID-19 vaccines has been of great interest and significance in the global fight against the pandemic. The United States of America recorded a daily average confirmed cases of one hundred and nine thousand, eight hundred and eighty-six (109,886) and death cases of one thousand and thirty-five (1035) during vaccination when infection was observed in larger people. This is followed by France, which recorded a daily average confirmed cases of forty-eight thousand, seven hundred and seventy-eight (48,778) and death cases of one hundred and thirty-two(132). However, South Africa recorded the lowest daily average confirmed cases of three thousand, five hundred and forty-five (3545)and seventy-five (75) deaths cases. From this study, it is evident that the ability of vaccines to curb the infection and incidence rates of COVID-19 is not apparent. Five of the six countries examined (India, France, Australia, the U.S.A., and Brazil) experienced a rapid increase in infection rates during the vaccination period compared to before. Only South Africa showed a reduction in infection rates during vaccination. Various factors may be responsible for the inability of vaccines to curb infection and incidence rates. One of the factors may be the emergence of the omicron (B.1.1.529) variant, first discovered in the UK in November 2021. There was evidence of reduced vaccine effectiveness against this variant [36]. Partial and complete relaxation of non-pharmaceutical interventions put in place by various governments because of the arrival of vaccines could also be a factor, as it has been established that vaccination alone is insufficient to contain the COVID-19 outbreak [10].

Additionally, all six countries demonstrated increased incidence rates during the vaccination period. However, the results indicate that vaccination has positively impacted the case fatality rate, representing the proportion of cases that eventually result in death. In all countries included in the study, the case fatality rate decreased during the vaccination period compared to the pre-vaccination period. These findings align closely with the report by [8], who also analyzed the effect of vaccines on infection and incidence rates of COVID-19 in five African countries. Notably, the analysis did not reveal any statistically significant difference in the means of the case fatality rate and infection rate before and during the vaccination period. De Martonne’s aridity index showed that India is classified as a “Wet region,” indicating higher precipitation. South Africa and Australia are classified as “Semi-arid regions,” suggesting relatively lower precipitation levels than wet regions. France, U.S.A., and Brazil are classified as “Very wet regions,” indicating significant rainfall.

This study also established a statistically significant relationship between the climatic conditions of the countries under investigation and the infection, incidence, case fatality, and Specific Mortality rates. This corroborates previous studies that temperature and humidity have been associated with the spread of COVID-19 [37, 38, 39].

5. Conclusion

The findings of this study indicate that vaccination has effectively reduced the case fatality rate in all countries under examination. However, infection rates have increased during vaccination in most countries, except South Africa. Moreover, incidence rates have increased across all countries during the vaccination phase. The risk of infection might also be influenced by climatic conditions since there are relationships between the Aridity Index and the incidence, infection, and case fatality rates, though not statistically significant. Based on the aridity index, South Africa and Australia belong to the Semi-arid regions. India belongs to the Wet region. France, U.S.A., and Brazil fall within the Very wet regions. Hence, the study underscores the importance of implementing non-pharmaceutical measures in conjunction with vaccination efforts to mitigate the rise in incidence and infection rates. Pearson correlation analysis also show there are no statistically significant linear relationships between the Aridity Index and Case fatality, Infection, Incidence, and Specific mortality rates for the two vaccination periods. In summary, this research offers valuable insights into the efficacy of COVID-19 vaccinations in diverse countries, emphasizing the significance of continued preventive measures to combat the ongoing pandemic effectively.

This study has certain limitations that should be considered. Firstly, the focus on leading countries (India, South Africa, France, Australia, the U.S.A., and Brazil) across continents may not fully represent the global population, and the findings may not apply to other countries or regions with distinct demographics, healthcare systems, or epidemiological characteristics. Additionally, the study’s concentration on the period during vaccination is essential to acknowledge, as vaccine rollout and coverage can vary significantly across countries and over time. Factors such as variations in vaccine distribution, uptake, and the emergence of new variants during the study period could influence the observed trends. It is vital to recognize that variants of the virus, disparities in vaccine coverage and distribution, and individual behaviors related to adherence to preventive measures could contribute to the intricate dynamics of COVID-19 transmission.

Based on the findings of this research, the following potential policy implications and recommendations can be considered:

Vaccination Strategies: Given the reduced case fatality rates during the vaccination period in most countries, emphasis should be placed on maintaining and expanding vaccination campaigns. Countries with successful vaccination programs (e.g., France and Australia) can serve as models for others, highlighting the positive impact on reducing case fatality rates.

Infection Control Measures: Despite vaccination efforts, some countries experienced an increase in infection rates during the vaccination period. Reinforcement or adaptation of infection control measures may be necessary. Continued promotion of preventive measures, such as mask-wearing, social distancing, and hygiene practices, could contribute to mitigating the spread.

Surveillance and Monitoring: Regular monitoring of case fatality rates, infection rates, and incidence rates is crucial for timely intervention and adjusting public health strategies. Ongoing research and surveillance can provide insights into the effectiveness of vaccines and help identify emerging trends.

Adaptation to Variants: Given the evolving nature of the COVID-19 virus, policies should be flexible and responsive to new variants. Research on the impact of variants on case outcomes is essential for informed decision-making.

Specific Mortality Considerations: Attention should be given to specific mortality rates, as they provide insights into the risk of death among diagnosed cases. Targeted interventions may be needed for populations at higher risk.

Global Collaboration: Countries with successful outcomes, such as Australia and France, can collaborate with others to share best practices, resources, and experiences. International cooperation on research and data-sharing can enhance the understanding of COVID-19 dynamics and improve global response strategies.

Communication Strategies: Effective communication strategies are essential to disseminate information about the importance of vaccination, preventive measures, and any changes in public health recommendations. Governments and health authorities should engage with the public to address concerns, provide accurate information, and encourage compliance with public health guidelines.

Research and Development: Continued investment in research is crucial for understanding the long-term impacts of COVID-19, vaccine efficacy, and the evolving nature of the virus. Research should concentrate on identifying factors that contribute to variations in case outcomes among different countries and populations.

It is however important to note that specific policy recommendations should take into account the unique circumstances and challenges faced by each country and should be guided by ongoing assessment of the local epidemiological situation.

Further research and continuous monitoring are necessary to acquire a more thorough understanding of the impact of vaccination on infection and incidence rates and to inform effective public health strategies for mitigating the pandemic. By considering these limitations and conducting additional investigations, we can refine our understanding of the efficacy of vaccination and its potential implications for global public health.