Cristina Gutiérrez Viloria
A recent study indicates that there are factors specific to each country and unrelated to the characteristics of COVID-19 patients that determine deaths from this disease.
After compiling data from 169 countries, researchers concluded that intensifying COVID-19 screening, improving government efficiency, and increasing hospital beds could mitigate mortality.
The researchers indicated that this is the first global cross-sectional study to systematically analyze, at the country level, the factors related to COVID-19 mortality. The study was conducted in Taiwan by Li-Ling Lian and Chun-Ying Wu and was published in Scientific Reports , a journal belonging to the Nature group.
Several studies highlight the existence of patient-level factors that could explain these deaths. These findings will undoubtedly help healthcare professionals identify high-risk patients, but they will not be sufficient to support effective policy measures to reduce COVID-19 mortality. According to the authors, a key issue in overcoming this pandemic is understanding the origin of the variability in mortality rates between countries, as it indicates factors beyond the patient's control, such as government response.
Closing the gap
Several studies have attempted to fill this knowledge gap by investigating the effectiveness of government policies in curbing the spread of the virus, forecasting hospital capacity to allocate resources to large numbers of patients, analyzing the association between mortality and the availability of healthcare resources, and promoting screening to minimize viral spread. However, not all of this data has yet been compared to explain the different mortality rates between countries. Therefore, the authors of this study delved deeper into the factors that could answer this question.
The study began with a sample of information from 169 countries obtained from different publicly accessible databases: the Worldometer website, the World Governance Indicators (WGI), the World Development Indicators (WDI), and the Logistics Performance Index. (LPI. The final study sample consisted of 7,724,530 patients infected with SARS-CoV-2 with 428,086 deaths.
To study whether the relationship between the mortality rate (n deaths per 100 COVID-19 cases) and the screening tests performed varied with country characteristics, a linear regression model was applied to the sample. Countries were classified by per capita income, government efficiency score, proportion of population ≥ 65 years, and number of hospital beds; each category was further divided into high, medium/moderate, and low status.
As screening increased, COVID-19 mortality decreased in high-income (r = -0.32; p = 0.015), middle-income (r = -0.28; p = 0.015) and low-income (r = -0.67; p = 0.002) countries, with a stronger trend observed in lower-income countries (Spain was classified in the high-income group).
To contextualize Spain's situation in relation to the pandemic, the analysis of epidemiological indicators for 25 countries of the European Union and the United Kingdom, dated September 13, highlighted a number of countries with a stable trend and another group with a worrying trend. This latter group is divided into two subgroups: a) countries with high notification and screening rates, infections among the young population, and low rates of severe cases and deaths, and b) the remaining countries (including Spain) with high case reporting among the older population and the consequent increase in severe cases, hospitalizations, and mortality. In week 37, and across the 25 countries, Spain ranks 10th in the screening rate per 100,000 people. However, it ranks first in 14-day case reporting, screening test positivity rate, and case reporting among the 65-79 age group. It also ranks second in reported cases among the population aged 80 and over, and in death rates (per 1,000,000 people over 14 days). Based on this data, it would be interesting to analyze which factors are not being controlled by screening in our country that cause us to be at the top of the list in these indicators.
También disminuyó la mortalidad al aumentar el cribado en los países con puntuaciones de eficiencia gubernamental moderada (r = -0,33; p = 0,021) y baja (r = -0,42; p = 0,002), en países con porcentaje moderado (r = -0,39; p = 0,006) y bajo (r = -0,67; p < 0,001) de personas de edad avanzada, y en países con menos camas de hospital (r = -0,41; p = 0,005).
Los análisis de regresión múltiple para predecir la mortalidad confirmaron esta correlación inversa entre mortalidad por COVID-19 y cribado. Así, la tasa de mortalidad de COVID-19 se asoció negativamente con el número de pruebas por cada 100 personas (RR: 0,92; p = 0,011), la puntuación de eficiencia gubernamental (RR: 0,96; p = 0,017), y el número de camas hospitalarias (RR: 0,85; p < 0,001).
Por otra parte, los factores que siguieron relación directa con la mortalidad fueron mayor proporción de la población ≥ 65 años (RR: 1,12; p < 0,011), y mejor infraestructura relacionada con el comercio y el transporte (RR: 1,08; p = 0,002). Según los investigadores, la infraestructura de transporte facilita la movilidad humana y la circulación de mercancías, lo que podría aumentar las transmisiones de COVID-19 entre las poblaciones de alto riesgo. En concordancia con esta idea, la proporción de casos importados en los países de la Unión Europea y Reino Unido notificados al European Surveillance System (TESSY) fue disminuyendo con los confinamientos y las restricciones de movimiento impuestas. Esto pondría de manifiesto la relevancia del control de fronteras para evitar la dispersión del virus.
Por otra parte, las tasas de mortalidad predichas por el modelo de regresión múltiple presentaron fuerte asociación con las tasas de mortalidad observadas (r = 0,77; p < 0,001), lo que sirvió para validar el modelo utilizado por los investigadores.
In short, the strongest correlation between higher mortality and lower numbers of diagnostic tests was found in low-income countries with lower government efficiency scores and fewer hospital beds. This suggests, according to the researchers, that increased diagnostic testing could be an effective approach to mitigating mortality in countries that have been less effective in controlling outbreaks, or where the number of hospital beds is insufficient. As the Organisation for Economic Co-operation and Development (OECD) points out in its proposal for managing the crisis at the government level, while the challenges and costs may be significant, they are not comparable to the consequences of a potential population lockdown. [ 12 ]
Furthermore, greater government efficiency was associated with lower COVID-19 mortality rates. While good governance is essential for long-term development outcomes, researchers have shown that in short-term crises like this, government efficiency is critical: acting proactively in developing policies that ensure the supply of protective equipment, implementing rapid and effective quarantine, lockdown, and screening policies, and being efficient in providing good public health services.
The researchers identified several limitations of the study, such as inaccurate reporting of COVID-19 cases by countries, which would affect the model's predictive power; incomplete data from certain countries (China, New Zealand, Indonesia); the lack of integrated patient-level data, which would strengthen the prediction; and herd immunity acquired through the spread of the virus, altering the prediction's accuracy. Even so, they stated that the results can still contribute to the formulation of national policies to address the pandemic.
Since they only selected a limited number of factors that determine mortality, they noted that future studies could be aimed at exploring additional country-specific factors.
"A syndemic, not a pandemic"
The idea underlying this article is in line with the recent editorial comment in The Lancet by Dr. Richard Horton, a physician and editor of the journal, in which he refers to the concept of COVID-19 as a syndemic rather than a pandemic, and the consequent misguided approach of governments to contain it: [ 15 ] Unlike the pandemic approach, which focuses on controlling viral transmission, a syndemic approach reveals biological and social interactions relevant to prognosis, treatment, and health policy, argued Merrill Singer in The Lancet in 2017. [ 15 ]
According to Dr. Horton, "there is an interaction between two types of diseases, COVID-19 and non-communicable diseases, which are defined in social groups following patterns of inequality deeply rooted in our societies." [ 16 ]
“Synergy in a context of social and economic disparity exacerbates the adverse effects of each factor individually. Addressing non-communicable diseases, a neglected cause in the poorest countries, will be a prerequisite for containing the coronavirus. The importance of viewing COVID-19 as a syndemic lies in highlighting its social origins and the worsening of its consequences for vulnerable populations. Unless governments coordinate policies to reverse deep disparities, the search for a purely biomedical solution will fail,” he stated.
From: https://espanol.medscape.com/verarticulo/5906110