Analysis of the Concept of Deaths per Million in the Impact Assessment of COVID-19 Pandemic in 2020

Abstract

The pandemic of the Coronavirus disease 2019 has been quite devastating. Assessing the success of the public health measures put in place by different nations has become a herculean task, especially as there is no effective index to determine that. The existing public health indices such as the Case fatality ratio and Mortality rate have not proven efficient in ascertaining the progress made in the early implementation of some public health measures. Hence, the index Deaths Per Million, an estimated mortality rate, is considered an alternative tool to ascertain the progress made at the onset and peak of the pandemic. In this case study, we have compared these three indices to know which best fits the pandemic. We also elucidated when and how deaths per million can be efficiently utilized during a pandemic to know the most appropriate time to impose lockdowns and other public health measures. This is considering the tendency for lockdowns to affect the psycho-social skills of humans and adversely impact economic activities both locally and globally. This work further provided evidence why the index Deaths Per Million is preferred during a pandemic over case fatality ratio and mortality. This was done using statistics from various countries for one year. These countries were selected based on their population and their peculiar nature.

1. Introduction

The COVID-19 pandemic has led to many unwarranted deaths that could have been averted if the necessary measures had been implemented early enough. The difficulty of implementing these measures at the right time could partly stem from the fact that there were no indices to determine the magnitude of the effects caused by this pandemic at the onset. Hence, many lives were lost, and many governments enacted policies that led to harsh economic situations.

During this early onset, many nations came up with innovative ideas for survival. Some chose to use vitamin C tablets and sources rich in this vitamin [1, 2], and others adopted vitamin D [3, 4]. Nevertheless, the world's major economies plummeted due to the decelerated economic activities, leading to an economic quagmire across the world. This economic woe emanating from the reduced rate of economic activities was partly precipitated by the inability to ascertain how many lives have been badly imparted at this early part of the pandemic leading to a pandemonium of a sort. This is mainly because existing indices such as case fatality ratio (CFR) and Mortality rate (MR) have proven unsuccessful in deciphering the extent of imparting whether by exact figures or approximated figures. Hence a need to propose an index that can be utilized in similar situations so as forestall the grounding of economic activities, which is the nerve activity of every nation.

In this study, which is partly a review, we have compared three terms: case fatality ratio, Mortality rate, and Deaths Per Million, a term introduced during this pandemic by the situation report room of the World Health Organisation (WHO). The period under study is from 1st January 2020 to 31st December 2020. The aim is to evaluate the efficacy of the public health measures of some selected countries using these indices to know the index that is the best fit for the early part of the pandemic.

2. A case of covid-19 in 2020

According to the WHO definition, the case fatality ratio (CFR) is the proportion of individuals diagnosed with a disease who die from that disease [5]. Thus, it estimates the severity among detected cases:

$$\text{Case Fatality ratio}\left(\mathrm{CFR},\text{in}\%\right)=\frac{\text{Number of deaths from specific disease}}{\text{Number of confirmed cases of specific disease}}\times 100$$E1

Attempts to use this index may not be very feasible, considering its definition and designation. Thus, the mortality rate (MR), which is time or interval-based, is defined as the number of deaths from a specific cause divided by the total number of the population in a state or country multiplied by 100,000 at a definite interval was brought into this context [6]. This can be mathematically represented as:

$$\text{Mortality rate}=\frac{\text{Number of deaths from specific cause}\left(\mathrm{D}\right)}{\text{Total number of}\mathrm{a}\text{defined population}\left(\mathrm{P}\right)}\times \mathrm{100,000}$$E2

The use of mortality rate may not also be feasible, as some disease outbreaks may persist beyond a definite time interval, say a year, as is the current case of the pandemic. Hence, the term deaths per million (DPM) may be more appropriate. This could be why the WHO introduced the deaths per million, via her situation report room, a term that might be relatively new to neophytes in public health. Thus, the need to analyze this term as a concept via available data from the situation report room of the WHO, using the Coronavirus disease 2019 (COVID-19) pandemic as a case study.

2.1 Analysis of the terms using available data

Analyzing the data to elucidate the definition involves studying the trend in which the figures follow. A case study of the trend in this pandemic gives a clue as to why the World Health Organisation adopted the term Deaths Per Million (DPM) during a pandemic. The CFR of 2.317 (see Table 1) presents Nigeria with many deaths higher than Russia, whose CFR is 1.430, and Australia, whose theirs is at 1.361 (see Table 1). However, Nigeria is known to have fewer deaths than Russia and Australia. This scenario indicates that though CFR could be used to determine death rates from diagnosed disease cases, it may not be the most appropriate tool during or after a pandemic, especially in an African setting, due to some factors, including laboratory testing capacity. The erroneous impression given by CFR led to considering the mortality rate as an index [5]. However, the mortality rate, which is strongly influenced by time, may not be appropriate. This makes the data for case fatality ratio and mortality rate in (Tables 1 and 2) inaccurate [5, 6]. The inaccuracy presented by these two indices limits their use during a pandemic. Hence, the Deaths Per Million (DPM), which estimates the mortality rate irrespective of time, maybe preferred in this context.

Countries	Total population	Total number of cases	Total number of deaths	Mortality rate	Case fatality ratio	Deaths per million
Australia	25,203,198	7,641	104	0.412	1.361	4.126
Brazil	211,049,527	1,274,974	55,961	26.516	4.389	265.156
China	1,433,783,686	85,190	4,648	0.324	5.456	3.241
India	1,366,417,754	528,859	16,095	1.178	3.0433	11.779
Nigeria	200,963,599	24,077	558	0.278	2.317	2.777
Russia	145,872,256	634,437	9,073	6.220	1.430	62.198
The USA	329,064,917	2,452,048	124,811	37.930	5.090	379.290
U.K	67,530,172	310,254	43,514	64.436	14.025	644.364
S/Africa	58,558,270	131,800	2,413	4.121	1.831	41.207

Table 1.

Total population and the total number of cases per selected country between January and June 2020.

A table showing the respective population of countries according to the statistics from the United Nations with their MR, CFR, and DPM as of 28th June 2020. Case Fatality Ratio (CFR) and Deaths Per Million (DPM) of the different countries with the largest population in their continents. India and China were added because India is next in demography, aside from China being the abode of the index case. The UK and South Africa were added due to the emergence of the second variant in these countries [7, 8].

Countries	Total population	Cumulative number of cases	Cumulative number of deaths	Mortality rate	Case fatality ratio	Deaths per million
Australia	25,203,198	28,296	908	3.603	3.209	36.027
Brazil	211,049,527	7,448,560	190,488	90.257	2.557	902.575
China	1,433,783,686	96,324	4,777	0.333	4.959	3.332
India	1,366,417,754	10,187,850	147,622	10.804	1.449	108.036
Nigeria	200,963,599	83,576	1,247	0.620	1.492	6.205
Russia	145,872,256	3,050,248	54,778	37.552	1.796	375.520
The USA	329,064,917	18,648,989	328,014	99.681	1.759	996.806
U. K	67,530,172	2,256,009	70,405	104.257	3.120	1,042.571
S/Africa	58,558,270	994,911	26,521	45.290	2.666	452.899

Table 2.

Total population and the total number of cases per selected country between July and December 2020.

A table showing the respective population of countries according to the statistics from the United Nations with their MR, CFR, and DPM as of 27th December 2020. Case Fatality Ratio (CFR) and Deaths Per Million (DPM) of the different countries with the largest population in their continents. India and China were added because India is next in demography, aside from China being the abode of the index case. The UK and South Africa were added due to the emergence of the second variant in these countries [8, 9].

According to the World Health Organisation, a COVID-19 death is a death emanating from a clinically compatible illness that is implicitly linked to a COVID-19 case, except when there is a clear alternative cause of death such as trauma which may not be linked to COVID-19 disease. In this case, there should be no gap between the time the patient completely recovers and when the patient dies [7]. This description favours the index called deaths per million (DPM) better than the other two indices. The term DPM could be described as the total number of deaths triggered at any time by the etiology of a pandemic or epidemic per 1,000,000 population of a country. In this instance, deaths from any cause occurring during the pandemic, which follows the description of the WHO, could be attributed to the pandemic [7, 10]. Though it is indicative and not confirmative, the deaths per million remains a crucial indicator of the actual effect of COVID-19 since it is not influenced by the errors in the certification of the causes of death [10]. This index is best fit for monitoring the efficiency of the control measures implemented by countries during a disease outbreak (Table 3). It helps to decipher when and where there would be a need for a total or partial lockdown during a pandemic or epidemic. It also helps to verify the progress made in saving lives, despite its limitation of only providing an estimate.

Week	Date	Number of cases	Number of deaths	Cumulative difference (deaths)	Deaths per million
1	1st October	59,001	1112	0	0
2	8th October	59,841	1113	1	0.005
3	15th October	60,982	1116	3	0.015
4	24th October	61,930	1129	13	0.065
5	29th October	62,521	1141	12	0.060
6	5th November	63,508	1155	14	0.070
7	12th November	64,728	1162	7	0.085
8	19th November	65,693	1163	1	0.005
9	26th November	66,974	1169	6	0.030
10	3rd December	70,669	1184	15	0.075
11	10th December	71,344	1190	6	0.030
12	17th December	76,207	1201	11	0.055
13	24th December	81,963	1242	41	0.204
14	31st December	87,510	1289	47	0.234

Table 3.

The deaths per million of the number of deaths recorded in Nigeria between 1st October to 31st December 2020.

With a total population of 200,963,599, Nigeria had a slight increase in her death toll during the festive period, as seen by her DPM. This could be due to reduced compliance with the COVID-19 protocols [11, 12, 13].

In Tables 1 and 2, one would think that the deaths per million (DPM) and the Mortality rate are the same indices or provide the same information. However, the definition of the Mortality rate presents a challenge in its use. Mortality rate, which may be defined as the number of deaths from a specific cause per 100,000 of the population of a state or a country per annum, may not be appropriate in the case of a pandemic, except if this definition is reviewed [6]. Hence the term deaths per million may be the most appropriate considering its flexibility of use.

The mathematical representation of Deaths Per Million (DPM) is:

$$\frac{\text{Total number of deaths related to the etiology of pandemic}\left(\mathrm{D}\right)}{\text{Total population of the country}\left(\mathrm{P}\right)}\times 1,000,000$$E3

It is important to note that this term can be applied to areas, regions, or states that have over a million population. For instance, states such as Lagos state in Nigeria, California in the United States, Moscow in Russia, Uttar Pradesh in India, Henan in China, and North-Rhine Westphalia in Germany may be described using DPM. While countries or states that have fewer than a million could be studied using the index such as Deaths Per Thousands (DPT) in a similar style [5].

3. Discussion

Understanding the importance of deaths per million as a public health tool is one of the major keys to outliving the pandemic. There are many ways in which this understanding of deaths per million can benefit man. However, this work focuses on its use in invoking lockdowns and in comparing the success rate of countries.

3.1 Decision-making process on lockdowns

The estimated mortality rate helps to know when to implement lockdowns. Lockdowns have their benefits; however, lockdowns pose some threats to the psycho-social well-being of man when imposed too frequently. A study done by researchers from the University of Pennsylvania noted that lockdowns led to the number of deaths related to COVID-19 plummeting by 33,000 deaths in the United States, as of 31st May 2020, a number showing 29% improvement in the fight against the virus. As of the same period, 3 million people were out of a job. They opined that implementing lockdowns which does not affect businesses could have saved more lives and a million jobs [14, 15]. The findings of some experts also supported the hypothesis of adverse effects of lockdown in the family. These findings revealed that due to the stress, job losses, anxieties, and other ill experiences are seen among families during the pandemic, restriction of movements (lockdown) could further exacerbate the rate of domestic violence and interpersonal violence, culminating in a spate of child abuse [15, 16, 17, 18].

Some authors argued that the aggravation of confirmed cases and mortality rates due to the COVID-19 pandemic negatively impacted mental health during the earlier part of the pandemic; hence, there was a need for a lockdown. These authors believed that the quality of air, water, and aquatic life was drastically improved during the restrictions of human activities. They, however, noted that the restrictions on movements led to economic disaster [19]. At the same time, some researchers think that lockdowns may reduce the rate of exposure to sunlight and alter daily social activities. A scenario that negatively imparts the circadian rhythms, culminating in poor health conditions and diminished psycho-social skills [20].

The importance of using the estimated mortality rate to determine when to call for lockdowns can never be overemphasized; this is because lockdowns create a lacuna in the daily operations and everyday lives of low-income earners. For instance, there was a rise in food scarcity in some parts of America and some countries in Sub-Saharan Africa due to the ill-planned policies on the restriction of movements [15, 21, 22, 23, 24, 25, 26, 27, 28]. Domestic violence grew across the globe during these lockdown periods [17, 29, 30, 31]. The birth rate in some low-income countries also grew, despite the limited resources [32]. At the same time, complications related to birth increased in some of these countries [32, 33]. Political instability and insecurity aggravated as terrorists, bandits and rogues maximized the opportunity of the lacunae created in the security apparel of nations in sub-Sahara Africa to re-strategize their modus operandi in perpetuating heinous activities [34, 35, 36, 37, 38]. For instance, the security agencies in Lagos, Nigeria, were overwhelmed with the reports of incessant attacks by criminals in this metropolitan state [39].

Deciphering the appropriate time to implement lockdowns remains a difficult decision for public health officials in many countries, sometimes leading to a debate. This debate could be resolved if one retrospectively analyses the experiences shared by some nations during the early part of the COVID-19 pandemic. For instance, Italy, with a population of 60,376,836, had her index case of COVID-19 in Rome on 31st January 2020 and the first death resulting from this disease on 21st February 2020, and by mid-March 2020, the number of deaths drastically rose, resulting in almost 50% of excess deaths from causes related to COVID-19 in March 2020 [10, 40, 41]. In this case, the total number of new deaths in Italy, which rose from 97 as of 10th March 2020 to 168 as of 11th March 2020, may not cause much panic [42, 43]. However, the statistics of 17th March 2020, which pegs the total number of deaths at 2503 as against the figure of 463 seen on 10th March 2020, calls for grave concern [42, 44]. Hence, ascertaining a weekly outcome may be worthwhile in deciphering the type and stringency of public health measures to be adopted. The estimated mortality rate of Italy presented a clearer picture of the success and compliance rate via this weekly analysis. The DPM of Italy, which was 7.67 as of 10th March 2020, and 41.46 as of 17th March 2020, shows an increase of 6-times fold and over 400% increase, a scenario that required urgent measures.

Considering the case of Italy, one could implicitly say that the DPM should be used to predict the appropriate time for a total or partial lockdown, bearing in mind the epidemic capacity or basic reproduction number (R₀) of the microbe. This is especially when the available data shows a 3-times fold and over 200% increase in the space of 7 days [40, 42, 43, 44]. Based on the information provided in Table 3, lockdowns should be implemented by week 13. This is due to the 270% increase seen between week 12 and week 13, as presented by the case study.

The suspension or ease of lockdowns should be considered when the DPM is closer to the lowest weekly figure, which was observed within 6 to 12 weeks prior to the week of a surge. In this instance, the week with the lowest value and the week when the policy is reviewed should have very little difference. Using Table 3 as a case study, it would be appropriate to aim at achieving the figures close to that of week 2 or week 8 after there has been a surge in week 14. If the percentage difference in the DPM of both weeks that are compared is between 30% and 100%, the state or country may consider a partial easing of the lockdowns, where only mass gatherings are suspended and public health measures enunciated by the WHO are upheld. If the difference in both weeks is between 2% and 30%, then the lockdown may be fully suspended while maintaining the guidelines of the WHO on non-pharmacological intervention. If the difference between both weeks is between 0% and 2%, then the pandemic may be declared over by the country's public health authorities after reaching a consensus with the WHO. Declaring the pandemic over requires consistency of between 0% and 2% in the cumulative difference of the weekly statistics for 6 to 12 consecutive weeks following the surge in cases. This shows that over 60% of the population of the state or country is already immunized against the virus in line with herd immunity and adaptive immunity.

Whenever it is difficult to ascertain the 0% to 2% fraction of the cumulative difference of DPM between the first time a lockdown is invoked in a country and the weeks preceding the review date, public health officials could make their deductions based on the topography of the country, the season of the year, the population size of the country, the characteristics of the microbes and the route of transmission of this microbial agent. In this case, the pandemic may be declared over only if, after 6 to 12 consecutive weeks, the cumulative difference in the weekly statistics of those still dying from this disease is less than or equivalent to a DPM of 0.01 and less than 2% of the population are reported to be diagnosed of the disease as seen in Table 3.

3.2 Ascertaining the success of public health measures

The estimated mortality rate helps to determine the success of the public health measures among a population, state, or country. Determining the success of the public health interventions helps instil confidence among the population, a feat that quells the panic attacks, which may obscure the actual situation in the control of these outbreaks [19]. Some health workers who were contacted via Facebook said they felt at ease when they realized that the rate of spread in Nigeria was not as rapid as what was happening in Italy and America as of March 2020. This was evident because, as of 17th March 2020, the DPM of Nigeria stood at zero. As of then, Nigeria had no deaths; Italy had 2503 deaths, making her DPM 41.46, while the United States of America, with 58 deaths, had an insignificant DPM [44].

DPM helps to know if the government and the people are compliant with the proven existing public health measures. India, which was very compliant with the rules in the early part of the pandemic in 2020, was taken unawares when it failed to comply with the public health measures during the second quarter of 2021 [45]. In the last quarter of 2020, Nigeria saw a slight increase in her DPM, when it lost a number of its top health workers partly because of non-compliance to the non-pharmacological interventions in preventing COVID-19 [11]. The data presented by the Nigeria Centre for Disease Control (NCDC) between October and December 2020 gave an insight into the fate of Nigeria, as presented in Table 3 [12]. The evidence provided in Table 3 gives credence to the utility of DPM as a veritable public health tool [12, 13].

4. Conclusion

The case fatality ratio (CFR) is the proportion of individuals diagnosed with a disease who die from that disease. The mortality rate (MR), which is time or interval-based, is defined as the number of deaths from a specific cause per a hundred thousand of the total population in a state or country. The deaths per million (DPM) is the total number of deaths emanating from a cause related to the etiology of a pandemic per a million of the total number of the population of a state or a country. While these indices all appear similar, the index, deaths per million, has a superior advantage in its use during pandemics; because it is not dependent on an interval, albeit its shortcoming of being an estimated value.

The index Deaths per million, which is an estimated mortality rate, is a relatively new term in the public health domain. It is expected to serve its purpose, especially during pandemics. This is considering how convenient it can be used in place of CFR and MR. Moreover, the use of this index proffers an economic advantage as it guides the public health officials in decision-making processes on movement restriction and monitoring of compliance rate, which influences economic activities. It also helps to determine states or countries that may be considered danger zones to enact the policies of International Health Regulations (IHR). In line with this, it is expected that public health agencies would judiciously utilize this index for the well-being of those they serve both now and in the future.

Acknowledgments

Special thanks to all the medical and health workers, the public health organizations, and their staff, who strive against all odds to bring succour to Africans during the pandemic.

Conflict of interest

The authors declare no competing interests.