Modelling risk using Bayes theorem of infection by antibiotic-resistant Escherichia coli in rural and urban populations of Ecuador

Introduction

For years, humankind has sought to mitigate the impacts produced by human development. Perhaps one of the most serious and unregulated problems in legislation is that of emerging pollutants (EP). According to Fernández et al. (2016)¹ these are common-use chemical compounds of natural or synthetic origin, which, despite not being considered significant in terms of distribution and/or concentration, present a risk to the environment and human health. Within EPs, antibiotics make up a group that is becoming increasingly important and their presence in the environment has become a global public health problem. Concern surrounding the presence of antibiotics in bodies of water and the subsequent increase in bacterial resistance has led the WHO to publish a list of bacteria that have developed capacities for inhibiting widely-used antibiotics. Bacterial resistance according to Rodríguez, A. (2016)² arises from the excessive and irrational use of antibiotics to treat infections that affect human beings’ bodies. This is due to an independent adaptive selection of the bacteria and the family of a specific strain as in the case of Staphylococcus aureus and its ability to inhibit conventional penicillin. This is not an isolated event; on the contrary, Cabrera, C. et al. (2007)³ maintain that by mutations in the chromosome of certain bacteria or by genetic exchange, bacteria can develop high innate resistance to antibiotics with several mechanisms between species of the same family or between different families. This study will explore the relationship that exists between bacterial resistance to antibiotics as a problem of emerging pollutants and public health for the inhabitants of Ecuador, taking area of residence as the reference.

Methods

In order to estimate the probability of an Ecuadorian contracting an antibiotic-resistant bacterial infection, one must consider the area where the person lives, the presence or absence of Escherichia coli in the main sources of water for human consumption in the country, and the antibiotic to be analysed (in this case ampicillin). The analysis was carried out considering the Bayes Theorem which, according to Marrero, D. (2014)⁴, is expressed as the conditional probability of a random event ‘A’ given another event ‘B’. Below is its formula, which takes into account that several events of A can be exclusive:

Where: P(A_i ) are the a priori probabilities.

P(B|A_i ) are the probabilities of B in hypothesis A_i.

P(A_i |B) are the a posteriori probabilities.

${\displaystyle {\sum }_{i=1}^{k}P(B|A_i)P(A_i)}$ is the sum of the probabilities of B in the hypothesis Ai times the a priori probabilities.

Our analysis focuses on the occurrence of three events:

Results

Conclusions

This study shows that both urban and rural populations are exposed to an antibiotic-resistant infection. However, Ecuador’s rural population is more exposed because the water sources they use are not safe. This draws attention to the necessity of providing safe, clean drinking water to the entire population. Even so, the high standards of water quality that many Ecuadorian cities have does not completely eliminate the risk of contracting antibiotic-resistant infections, thus demonstrating that an urgent legislation reform is required in order to control the release of these types of pollutants into bodies of water.

Data availability

Population and water quality data was obtained from the Instituto Nacional de Estadística y Censos (INEC), Population census (2010): http://www.ecuadorencifras.gob.ec/base-de-datos-censo-de-poblacion-y-vivienda/ and INEC, Survey (2016): http://www.ecuadorencifras.gob.ec/documentos/web-inec/EMPLEO/2017/Indicadores%20ODS% 20Agua,%20Saneamiento%20e%20Higiene/ Presentacion_Agua_2017_05.pdf