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Fighting Communicable Diseases
The United Nations Sustainable Development Goal 3 focused on the enhancement of the health and wellbeing of the people. Among the issues addressed through this SDG is the control of communicable diseases. This class of diseases comprises ailments that are transmissible from one person to another. Thus, epidemiological concepts are applicable in the control of these diseases, thus delineating the centrality of epidemiology in achieving SDG 3. Epidemiological studies are crucial in identifying the risk factors, making conclusions about the causative agents, and identifying the population at risk. Subsequently, it is possible to analyse the findings and make informed decisions about the interventions to take in preventing or treating communicable diseases. An example of an epidemiological study presented in this paper investigated the correlation between poverty and the incidence rate of pulmonary tuberculosis. Through this multicity study, the researchers were able to demonstrate the strength of the association between the two variables.
The United Nations member states ratified the Sustainable Development Agenda in September 2015 thereby establishing 17 Sustainable Development Goals (SDGs) for fulfilment in 2030. Among the 17 SDGs, goal 3 was to promote health and enhance wellbeing. Under this SDG, the United Nations aimed at, among other things, fighting communicable diseases by 2030 (Katila et al., 2019, xv). Communicable diseases are ailments that are transmissible from one person to another through various modes. A common example of communicable disease is COVID-19 which is transmissible through droplets from one person to another. Other communicable diseases are HIV/AIDS, Tuberculosis, Malaria, and Influenza. Thus, the United Nations aspired to address communicable diseases by establishing policies that would ensure the prevention, and treatment of these diseases by 2030.
Communicable diseases have global, national, and regional incidences. The prevalence of these diseases varies across the globe depending on the geography, customs, and economic activities. For example, water-borne diseases like enteric fever are common in places with poor sanitation. Additionally, the climate of a place determines the prevalence of certain communicable diseases. Malaria, for instance, is highly prevalent in regions that support the breeding of mosquitos. Such regions have high humidity and temperature, meaning that it is not possible to find malaria in temperate zones of the world. In the same vein, areas that lie along the equator have the ideal climate for mosquito breeding, making the prevalence of this disease high in countries such as Uganda, Bangladesh, and some South American countries.
Socioeconomic activities also influence the distribution of communicable diseases. Being a sexually transmitted disease, HIV/AIDS is highly prevalent among sex workers regardless of geographical location. Similarly, the prevalence of some water-borne diseases is relatively higher among communities that cultivate rice. The paddy conditions necessary for the cultivation of rice provide conditions for the breeding of vectors such as mosquitos that transmit Japanese Encephalitis Virus (Franklinos et al., 2019, e306). In addressing communicable diseases from a social or economic perspective, it is, therefore, essential to consider the alternatives available to avoid affecting the livelihoods of the people.
Besides fighting communicable diseases, SDG 3 has other targets that inform the prevention of infections in the community. Another target of SDG 3 is to reduce infant and child mortality. Communicable diseases are some of the causes of infant and child mortality. Neonatal sepsis, for example, can result from the cross-infection of the mother or the birth environment. At the same time, vaccine-preventable diseases like meningitis cause high mortality among children. Therefore, it is crucial to integrate the fight against communicable diseases with other targets under SDG 3. The government and other concerned stakeholders are called to institute holistic measures that do not focus on one sub-section of this SDG. Rather, the policies and interventions should consider the myriad causative factors that lead to communicable diseases and thus customize them according to the needs of the population. Methods to increase uptake of vaccines in children, control of waterborne infections, and better nutrition are some of the measures that cut across more than one target of SDG 3. This essay discusses epidemiological study designs and reviews an ecological study correlating poverty and tuberculosis disease burden in Brazil.
Correlation between Tuberculosis and Poverty
Tuberculosis is one of the commonest communicable diseases in developing nations. It accounts for high mortality every year. According to the World Health Organization (2021), TB took the lives of 1.5 million people in 2020. A significant percentage of this number was people living with HIV/AIDS. Therefore, the disease burden from TB calls for investment in research on prevalence as well as the social determinants of health. Through epidemiological studies, it is possible to correlate TB with one or more social determinants of health.
VanderWeele et al. (2020) define epidemiology as “the study of the distribution and determinants of health-related states and events” (189). Therefore, epidemiological concepts applicable in fighting communicable diseases include the frequency, pattern of distribution, and causative factors of communicable diseases. For instance, a high incidence rate in a particular area means that the caseload is high and so is the frequency. The frequency of the disease offers insightful ideas about the virulence of the causative agents, the immunity of the population, and other social or economic factors that may lead to the observed statistics.
Poverty is one of the social determinants of health. Poverty mainly results from low income which makes it difficult to afford basic needs like shelter, food and clothing. Research on poverty has generated several theories that explain the source of poverty. Behavioural theory, for example, states that poverty emanates from “engaging in counter-productive, poverty-increasing behavior or “risks” like single motherhood or unemployment” (Brady, 2019, 4). The presence of poverty in people having these demographic characteristics serves to support this suggestion. On the same note, poverty may result from political causes such as unequal distribution of resources (Brady, 2019, 16). Concerning communicable diseases, poverty predisposes communities to a wide range of infectious conditions like malaria, typhoid, TB, and HIV/AIDS. Zille et al. (2019) conducted an epidemiological study to determine the association between pulmonary tuberculosis and poverty in a Brazilian population.
The above study aimed to correlate social status with TB-specific variables such as loss to follow-up, incidence rate, cure, treatment, mortality, and recurrence (Zille et al., 2019, 2). Similar studies conducted in Brazil focused on specific towns and municipalities, but Zille et al. (2019) aimed at gathering national data to expand the scope of the study. Thus, the findings of this study represent the mentioned variables in 5560 municipalities. The study population was the entire country where all the municipalities were included. The researchers stratified the cities as small, medium, and large. They defined small cities as having a population density of up to 80 people per square kilometre, and above this number for medium cities. Large cities are those with more than 10000 inhabitants regardless of the population density.
Poverty was the main exposure measured in this study. The researchers used the human development index (HDI) and Gini Index (GI) to measure the level of poverty. Gini Index is a “globally used indicator that enables analyzing the socioeconomic situation of the population, identifying segments that require greater attention from public health policies, as well as education and social protection, among other factors” (Zille et al., 2019, 2). In other words, GI measures poverty as a socio-economic outcome. On the other hand, the Human Development Index considers three factors relevant to the quality of life. Thus, it is a measure of longevity, education, and income status. Using the two measures, the researcher could categorize the population to identify the different levels of socioeconomic status.
The study design was ecological. This design relates the variables with places rather than individuals. The data for analysis comes from a “population case series” (Bhopal, 2019, 315). Bhopal (2019) argues that all epidemiological studies are ecological since they deal with establishing data from large populations. In most cases, data for this study come from national or regional registries. In the study conducted by Zille et al. (2019), data on TB incidence rates, loss to follow-up, cure, treatment, and recurrence was derived from different Brazilian information databases. For example, the Department of Statistics of the Unified Health System (DATASUS) generated information on GI, incidence rates, and mortality while the United Nations Program for Development (UNDP) served as the source of data on HDI. In sum, this study design was appropriate for the research objectives due to the large data sizes required.
The main result was the negative correlation between PTB incidence rate and HDI. In other words, the higher the HDI, the lower the PTB incidence rates and vice versa. However, the strength of this correlation varied depending on the city size, with small and medium cities showing a weak correlation. HIV infection is a confounder in the correlation between PTB and HDI. The researcher controlled for this confounder by using HIV infection rate as a predictor variable. There was no bias identified in this study. The tests of significance conducted during data analysis showed that the results were not merely by chance. The correlation coefficients for PTB incidence rate, HDI, and GI were -0.42 and 0.44 respectively. These values prove that the correlation between the PTB and the two measures of socioeconomic status is significant, meaning that poverty is a strong predictor of PTB in Brazil.
These results are generalizable to populations other than the one used in the study. Indeed, poverty predisposes people to myriad diseases. Pulmonary TB, for example, is acquired through exposure to respiratory droplets bearing the bacteria that causes the disease. A person may contract this disease especially when they are immune-compromised. Poverty prevents the consumption of meals that may help boost immunity, meaning that some poor people may live in a state of low immunity. Homelessness and living in the streets expose people to TB through the inevitable contact with positive cases. Lack of money to seek medical care can also exacerbate mild conditions leading to mortality from a curable disease like tuberculosis. In sum, poverty always predisposes a population to communicable diseases.
Applications and Recommendations
Epidemiological research for communicable diseases has taken a new momentum, especially after the outbreak of COVID-19. Epidemiological studies focus on not only the disease but also the risk factors, transmissibility, spread, and case fatality. From these studies, it is evident that epidemiological studies are useful in the research efforts towards understanding an outbreak or the rise of cases of a disease like tuberculosis. Communicable diseases may emanate from many sources. Respiratory transmission, like in the case of TB, calls for a prompt investigation into the causative agent, disease pattern, and most importantly, the correlation between risk factors and the incidence rate of a disease.
Formulating policies on TB prevention relies on epidemiological information generated through scientific studies. The policy must have a strong basis of formulation if any results are to come from this intervention. The people making the policy demand to know what are the expected outcomes of the funding that goes into resolving a specific public health issue. In fighting communicable diseases, various policies have been put in place at national, regional, and international levels. Governments depend on scientific evidence to roll out national policies in combating communicable diseases. In Bangladesh, for example, an epidemiological study involving the use of a spatial analysis framework identified the factors leading to low TB detection and treatment in the country. One of the findings in this study was that poverty was negatively correlated with the reporting and treatment of TB in Bangladesh (Rood et al., 2019, 5). This finding thus helps the government to customize policies that will increase the reporting of suspected TB cases among the poor communities. It is recommended, therefore, that the government funds nationwide epidemiological research that helps to understand the disease pattern before making policies to address communicable diseases. Moreover, the correlation between poverty and tuberculosis means that the government should address the prevalence of this disease by first findings ways to resolve socioeconomic disparities in the country.
The global disease burden from communicable diseases remains high, calling for concerted efforts in combating ailments such as TB. To study communicable diseases, epidemiological concepts such as incidence, prevalence, and distribution are essential. These concepts offer an all-around comprehension of the disease, thus helping in improvising prevention and treatment measures. Fighting communicable diseases, as one of the agendas under UN SDG 3, requires conducting epidemiological research. This research informs the formulation of policies by the government and other concerned bodies. The research must fulfill one of the three purposes of epidemiological studies. It should ideally identify the causative agents, quantify the disease burden, or predict the risk of future transmission. The policies enacted by the government should be based on scientific evidence for them to yield the desired fruits.