Excess (Preventable) Mortality as a Marker of the Quality of Governance in Disaster

“AUTHORITIES MAY BE RELUCTANT TO ESTABLISH ACCURATE MORTALITY FIGURES WHEN THEY HAVE BEEN SLOW TO ACT ON EARLY WARNINGS.” (1)

Basic Principles in Infectious Disease Epidemiology:

Infectious disease epidemiology is based on 3 main elements (the epidemiological triad), an external ‘agent’ (bacteria or virus), a susceptible ‘host’ (animal or human) and the ‘environment’. Interaction between the susceptible host and the agent causes the disease to occur in the host. However, this model is applicable to any hazard where the 3 elements coexist. (earthquake, hurricane, famine, whatever).

A fourth but not essential element in infectious disease is a ‘vector’, which is an organism that transmits infection by conveying or transmitting the agent (pathogen) from one host to another, without causing disease itself. In the case of COVID-19, SARS-CoV-2 is the agent, humans are the host, and the vector is the bat or the Pangolin (anteater). Every infectious disease agent can be transmitted to other hosts. The ease with which transmission or contagion occurs is called the reproductive number, the R-naught (Ro). SARS-2 has a Ro of between 1-3. Each infected person can pass the disease to 3 other susceptible individuals or even animals.

Health Indicators:

It is also important to quantify a variety of health ‘indicators’ that serve to determine the scope and the impact of a given hazard or disease on a population at risk. For example, there are indicators that serve to quantify the number of new cases in a population at risk (incidence) or the total number of cases in the population at risk (prevalence) at any given time, or the evolution of new cases (disease monitoring or disease surveillance), as well as a rate that serves to quantify the efficacy of interventions both medical (therapeutic) and/or public health (containment, social distancing, masks, etc.) on fatalities (the case fatality rate).

These indicators usually consist of a simple calculation, a ratio, with a numerator and a denominator. For example, in this pandemic the case fatality rate consists of the # of patients who died of COVID/total # of COVID cases (all those infected) within the defined population.
The mortality rate is the total # of deaths from the infectious disease/total population, infected or not. The case fatality and the mortality rates can be further stratified to examine the impact of age (age-specific mortality) or associated risk factors (co-morbidities), or a number of other factors that affect the host (infected person).

Excess Mortality: Scientific implications

A useful indicator to determine the severity of impact of a pandemic or other disaster on the affected population is the ‘excess mortality’, defined as, the number of deaths which occurred in a given crisis above and beyond what we would have expected to see under ‘normal’ conditions. For example, the 2017 Hurricane Maria in Puerto Rico produced excess mortality above and beyond what would have been expected from all other causes during the period of the Hurricane compared to a period (usually the year before) when there was no Hurricane.

Excess Mortality: Political Implications

According to Tierney (2), “disaster governance consists of the interrelated sets of norms, organisational and institutional actors, and practices (spanning pre-disaster, trans-disaster, and post-disaster periods) that are designed to reduce the impacts and losses associated with disasters arising from natural and technological agents and from intentional acts of terrorism.”

In this vein excess mortality may also be defined in political terms, based on the quality of actions taken by government authorities. A failed government response will result in ‘preventable’ mortality in excess of what would have been expected had government acted appropriately and in good faith. In order to judge the timeliness, appropriateness, adequacy, and outcome of the governments actions in a disaster, a comprehensive and systematic evaluation of the government’s role must be undertaken after the event. More often than not governmental failure in disaster is due to inept leadership resulting in untimely warning, poor planning and preparation, limited or no organization, inappropriate or delayed response, disorganized or chaotic implementation of the relief/response effort, or all the above.

Guha-Sapir et al (1), describe the politics of death tolls in disaster. As an example, they report on the death toll after the 2017 Hurricane in Puerto Rico. President Donald Trump downplayed the severity of the event by grossly underestimating the death toll, suggesting there were only 66 deaths, and attributing low mortality to rapid response, despite official early estimates strongly suggesting there were hundreds or even thousands of dead due precisely to a grossly delayed and inadequate response on the part of his administration. A subsequent academic study uncovered close to 4,000 dead, more than 46 times Trump’s estimate.

In the COVID Pandemic during the fall and winter of 2019-2020 respectively, Presidents Xi Jinping and Donald J. Trump both attempted to downplay the impact of the event. (https://www.vox.com/2020/5/14/21257247/trump-coronavirus-death-stats — https://www.nytimes.com/2020/01/26/world/asia/china-coronavirus-xi-jinping.html).

Historically, there have been many other examples of leaders manipulating death toll data in disaster for political expediency. The 1986 Chernobyl disaster in the former Soviet Union is another classic example of negligent governance in disaster.

In conclusion, failed or negligent disaster governance and response can be as lethal or more so than the disaster itself contributing to excess (preventable) deaths.

1- Guha Sapir, V. Science and Politics of Disaster Death Tolls, BMJ 2018;362:k4005 doi: 10.1136/bmj.k4005 – Published 24 September 2018.

2- Tierney, K. 2012. “Disaster Governance: Social, Political, and Economic Dimensions.” Annual Review
of Environment and Resources 37: 341-363. doi: 10.1146/annurev-environ-020911-095618)