Health safety nets can break cycles of poverty and disease: a stochastic ecological model

Modeling the synergistic interplay between malaria dynamics and economic growth

The mosquito-borne disease (malaria) imposes significant challenges on human health, healthcare systems, and economic growth/productivity in many countries. This study develops and analyzes a model to understand the interplay between malaria dynamics, economic growth, and transient events. It uncovers varied effects of malaria and economic parameters on model outcomes, highlighting the interdependence of the reproduction number (R0) on both malaria and economic factors, and a reciprocal relationship where malaria diminishes economic productivity, while higher economic output is associated with reduced malaria prevalence. This emphasizes the intricate interplay between malaria dynamics and socio-economic factors. The study offers insights into malaria control and underscores the significance of optimizing external aid allocation, especially favoring an even distribution strategy, with the most significant reduction observed in an equal monthly distribution strategy compared to longer distribution intervals. Furthermore, the study shows that controlling malaria in high mosquito biting areas with limited aid, low technology, inadequate treatment, or low economic investment is challenging. The model exhibits a backward bifurcation implying that sustainability of control and mitigation measures is essential even when R0 is slightly less than one. Additionally, there is a parameter regime for which long transients are feasible. Long transients are critical for predicting the behavior of dynamic systems and identifying factors influencing transitions; they reveal reservoirs of infection, vital for disease control. Policy recommendations for effective malaria control from the study include prioritizing sustained control measures, optimizing external aid allocation, and reducing mosquito biting.

Health Risk, Income Effect, and the Stability of Farmers' Poverty Alleviation in Deep Poverty Areas: A Case Study of S-County in Qinba Mountain Area

Health status and income level are both important factors in reducing poverty and accomplishing sustainable development in deep poverty areas of China. Therefore, the purpose of this study is to provide policy support for the sustainable poverty alleviation of farmers by analyzing the net effect of health risk on Farmers' income poverty and its impact mechanism. Based on the data of more than 199,000 farmers, this study uses the Difference in Difference (DID) model to empirically analyze the effect of health-risk on farmers' income poverty. The empirical findings obtained from DID model show that health risk has a significant and positive impact on income poverty, where the impact of disability is higher. Furthermore, the mechanism shows that the impact of health risks on income poverty is mainly influenced by farmers' off-farm working choices and time. The heterogeneity analysis shows that the health risk significantly impacts non-vulnerable farmers' poverty. With outdated healthcare facilities in poverty-stricken areas, people are more likely to fall into income poverty. Therefore, the study concludes that establishing an effective long-term mechanism of health risk prevention is essential to improving the endogenous development power of poor farmers and decreasing income poverty.

Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors

Zoonotic diseases spread through pathogens-infected animal carriers. In the case of Ebola Virus Disease (EVD), evidence supports that the main carriers are fruit bats and non-human primates. Further, EVD spread is a multi-factorial problem that depends on sociodemographic and economic (SDE) factors. Here we inquire into this phenomenon and aim at determining, quantitatively, the Ebola spillover infection exposure map and try to link it to SDE factors. To that end, we designed and conducted a survey in Sierra Leone and implement a pipeline to analyze data using regression and machine learning techniques. Our methodology is able (1) to identify the features that are best predictors of an individual’s tendency to partake in behaviors that can expose them to Ebola infection, (2) to develop a predictive model about the spillover risk statistics that can be calibrated for different regions and future times, and (3) to compute a spillover exposure map for Sierra Leone. Our results and conclusions are relevant to identify the regions in Sierra Leone at risk of EVD spillover and, consequently, to design and implement policies for an effective deployment of resources (e.g., drug supplies) and other preventative measures (e.g., educational campaigns).

Effects of social-distancing on infectious disease dynamics: an evolutionary game theory and economic perspective

We propose two models inspired by the COVID-19 pandemic: a coupled disease-human behaviour (or disease-game theoretic), and a coupled disease-human behaviour-economic model, both of which account for the impact of social-distancing on disease control and economic growth. The models exhibit rich dynamical behaviour including multistable equilibria, a backward bifurcation, and sustained bounded periodic oscillations. Analyses of the first model suggests that the disease can be eliminated if everybody practices full social-distancing, but the most likely outcome is some level of disease coupled with some level of social-distancing. The same outcome is observed with the second model when the economy is weaker than the social norms to follow health directives. However, if the economy is stronger, it can support some level of social-distancing that can lead to disease elimination.

Mitigating the externality of diseases of poverty through health aid

Externality exists in healthcare when an individual benefits from others being healthy as it reduces the probability of getting sick from illness. Healthy workers are considered to be the more productive labourers leading to a country's positive economic growth over time. Several research studies have modelled disease transmission and its economic impact on a single country in isolation. We developed a two-country disease-economy model that explores disease transmission and cross-border infection of disease for its impacts. The model includes aspects of a worsening and rapid transmission of disease juxtaposed by positive impacts to the economy from tourism. We found that high friction affects the gross domestic product (GDP) of the lower-income country more than the higher-income country. Health aid from one country to another can substantially help grow the GDP of both countries due to the positive externality of disease reduction. Disease has less impact to both economies if the relative cost of treatment over an alternative (e.g. vaccination) is lower than the baseline value. Providing medical supplies to another country, adopting moderate friction between the countries, and finding treatments with lower costs result in the best scenario to preserve the GDP of both countries.

Modeling coupling dynamics between the transmission, intervention of COVID-19 and economic development

Current explosive outbreak of the novel coronavirus (COVID-19) pandemic is posing serious threats to public health and economics around the world. To clarify the coupling mechanism between this disease and economic development, a new dynamical system is established by ordinary differential equations (ODEs). It is theoretically proved that the basic reproduction number is a nonlinear combination of parameters regarding disease transmission, intervention and economy effect, which totally determines the stability of the disease-free and endemic equilibria. Further analyses indicate the existence of interaction and mutual restraint among transmissibility, quarantine and economics, in which (1) COVID-19 would cause a long-term impact on halting economic progress; (2) strong coupling of COVID-19 and economics would easily trigger disease outbreak, cause more human infections and alleviate the intervention effects of quarantine; and (3) there exists optimal strategy of time-varying quarantine for disease control and economic development. It is highlighted that adaptive isolation (rather than constant isolation) of at-risk population (rather than random individuals) is highly effective in reducing morbidity at the cost of least economic loss.

Healthcare Safety Nets during the COVID-19 Pandemic Based on Double Diamond Model: A Concept Analysis

The purpose of this study was to analyze the concept of the "healthcare safety net" during the COVID-19 pandemic. Walker and Avant's process of concept analysis was used in this systematic literature review. The attributes of the concept of a healthcare safety net during the COVID-19 pandemic were found to be: (a) capacity, (b) accessibility, (c) health equality, and (d) education. In consideration of these defining criteria, antecedents to the concept were identified as: (a) the COVID-19 pandemic, (b) health inequalities (internal factors and external factors), and (c) healthcare systems (health insurance, screening, protective equipment, medicine, and medical services). Consequences of the concept were: (a) meeting healthcare needs, (b) quality of life, and (c) a decrease in morbidity and mortality. A healthcare safety net is an important concept during the COVID-19 pandemic. In situations like COVID-19, healthcare safety nets are designed to meet safety needs, improve quality of life, and reduce patient turnover and mortality. Based on the results of this study, the development of standardized tools for measuring a healthcare safety net as well as that of policies and systems for resolving a healthcare safety net in the COVID-19 situation is recommended.

Health, income and poverty: evidence from China's rural household survey

Background

Understanding the health status of the poor households and the influence of unhealthy on their income can provide some vital insights into the effectiveness and appropriateness of poverty reduction solutions.

Methods

Based on a nationwide cross-sectional survey of 29,712 rural poor households, this study systematically investigated the causes of poverty and health status of Chinese rural poor households, and revealed the relationship between health, income and poverty.

Results

The health status of the rural poor in China is not optimistic, with 51.63% attributing their poverty to the illness of household members. NCDs are the biggest health threat to the rural poor in China. Over 60% of all the households have at least one patient and more than a quarter of the households with patients cannot afford expensive medical expenses. Although 98% of all the households participate in China’s a rural health insurance system - the New Rural Cooperative Medical Scheme - 16% are still unable to bear their medical expenses after reimbursement from the scheme. Further, high altitude, ill-health and low-income are interlinked and mutually reinforcing. The per capita net income of poor households was inversely proportional to the altitude of their places of residence, family aging and unhealthy status, but was positively correlated with the number of workforces in their families.

Conclusions

Poverty due to illness is one of the root causes of rural poverty in China. With the backward medical infrastructure in high altitude areas, people are more prone to fall into the vicious circle of poverty-unhealthy-low income-poverty. The establishment of effective long-term mechanism of disease prevention and intervention is an important prerequisite to enhance the endogenous development power of the poor and reduce poverty.

Inequalities in the social determinants of health and Chagas disease transmission risk in indigenous and creole households in the Argentine Chaco

Background

The social determinants of health (SDHs) condition disease distribution and the ways they are handled. Socio-economic inequalities are closely linked to the occurrence of neglected tropical diseases, but empirical support is limited in the case of Chagas disease, caused by the protozoan Trypanosoma cruzi. Herein we assessed the relationship between key structural SDHs and the risk of T. cruzi vector-borne transmission in rural communities of the Argentine Chaco occupied by creoles and an indigenous group (Qom). We used multiple correspondence analysis to quantify the household-level socio-economic position (social vulnerability and assets indices), access to health and sanitation services, and domestic host availability. We identified the most vulnerable population subgroups by comparing their demographic profiles, mobility patterns and distribution of these summary indices, then assessed their spatial correlation and household-level effects on vector domiciliary indices as transmission risk surrogates.

Results

Qom households had higher social vulnerability and fewer assets than creoles, as did local movers and migrant households compared with non-movers. We found significantly positive effects of social vulnerability and domestic host availability on infected Triatoma infestans abundance, after adjusting for ethnicity. Access to health and sanitation services had no effect on transmission risk. Only social vulnerability displayed significant global spatial autocorrelation up to 1 km. A hotspot of infected vectors overlapped with an aggregation of most vulnerable households.

Conclusions

This synthetic approach to assess socio-economic related inequalities in transmission risk provides key information to guide targeted vector control actions, case detection and treatment of Chagas disease, towards sustainability of interventions and greater reduction of health inequalities.

Electronic supplementary material

The online version of this article (10.1186/s13071-019-3444-5) contains supplementary material, which is available to authorized users.

Healthcare, Health, and Income

The medicalization model of poverty leads us to devote considerable resources to treating the healthcare problems caused by poverty while neglecting the root cause of those problems - the poverty itself. Treating symptoms rather than causes is far less effective than treating causes. When correctly understood, poverty is a major public health problem that needs to be addressed directly with effective anti-poverty programs. Only then can we properly serve the healthcare needs of the poor.

General ecological models for human subsistence, health and poverty

The world's rural poor rely heavily on their immediate natural environment for subsistence and suffer high rates of morbidity and mortality from infectious diseases. We present a general framework for modelling subsistence and health of the rural poor by coupling simple dynamic models of population ecology with those for economic growth. The models show that feedbacks between the biological and economic systems can lead to a state of persistent poverty. Analyses of a wide range of specific systems under alternative assumptions show the existence of three possible regimes corresponding to a globally stable development equilibrium, a globally stable poverty equilibrium and bistability. Bistability consistently emerges as a property of generalized disease-economic systems for about a fifth of the feasible parameter space. The overall proportion of parameters leading to poverty is larger than that resulting in healthy/wealthy development. All the systems are found to be most sensitive to human disease parameters. The framework highlights feedbacks, processes and parameters that are important to measure in studies of rural poverty to identify effective pathways towards sustainable development.

Domestic dog health worsens with socio-economic deprivation of their home communities

Dogs play an important role in infectious disease transmission as reservoir hosts of many zoonotic and wildlife pathogens. Nevertheless, unlike wildlife species involved in the life cycle of pathogens, whose health status might be a direct reflection of their fitness and competitive abilities, dog health condition could be sensitive to socio-economic factors impacting the well-being of their owners. Here, we compare several dog health indicators in three rural communities of Panama with different degrees of socio-economic deprivation. From a total of 78 individuals, we collected blood and fecal samples, and assessed their body condition. With the blood samples, we performed routine hematologic evaluation (complete blood counts) and measured cytokine levels (Interferon-γ and Interleukin-10) through enzyme-linked immunosorbent assays. With the fecal samples we diagnosed helminthiases. Dogs were also serologically tested for exposure to Trypanosoma cruzi and canine distemper virus, and molecular tests were done to assess T. cruzi infection status. We found significant differences between dog health measurements, pathogen prevalence, parasite richness, and economic status of the human communities where the dogs lived. We found dogs that were less healthy, more likely to be infected with zoonotic pathogens, and more likely to be seropositive to canine distemper virus in the communities with lower economic status. This study concludes that isolated communities of lower economic status in Panama may have less healthy dogs that could become major reservoirs in the transmission of diseases to humans and sympatric wildlife.

Poverty, disease, and the ecology of complex systems

Understanding why some human populations remain persistently poor remains a significant challenge for both the social and natural sciences. The extremely poor are generally reliant on their immediate natural resource base for subsistence and suffer high rates of mortality due to parasitic and infectious diseases. Economists have developed a range of models to explain persistent poverty, often characterized as poverty traps, but these rarely account for complex biophysical processes. In this Essay, we argue that by coupling insights from ecology and economics, we can begin to model and understand the complex dynamics that underlie the generation and maintenance of poverty traps, which can then be used to inform analyses and possible intervention policies. To illustrate the utility of this approach, we present a simple coupled model of infectious diseases and economic growth, where poverty traps emerge from nonlinear relationships determined by the number of pathogens in the system. These nonlinearities are comparable to those often incorporated into poverty trap models in the economics literature, but, importantly, here the mechanism is anchored in core ecological principles. Coupled models of this sort could be usefully developed in many economically important biophysical systems--such as agriculture, fisheries, nutrition, and land use change--to serve as foundations for deeper explorations of how fundamental ecological processes influence structural poverty and economic development.

Clusters of poverty and disease emerge from feedbacks on an epidemiological network

The distribution of health conditions is characterized by extreme inequality. These disparities have been alternately attributed to disease ecology and the economics of poverty. Here, we provide a novel framework that integrates epidemiological and economic growth theory on an individual-based hierarchically structured network. Our model indicates that, under certain parameter regimes, feedbacks between disease ecology and economics create clusters of low income and high disease that can stably persist in populations that become otherwise predominantly rich and free of disease. Surprisingly, unlike traditional poverty trap models, these localized disease-driven poverty traps can arise despite homogeneity of parameters and evenly distributed initial economic conditions.

Disease ecology, biodiversity, and the latitudinal gradient in income

Vector-borne and parasitic diseases are drivers of the latitudinal gradient in income, and the burden of these diseases is predicted to rise as biodiversity falls.

While most of the world is thought to be on long-term economic growth paths, more than one-sixth of the world is roughly as poor today as their ancestors were hundreds of years ago. The majority of the extremely poor live in the tropics. The latitudinal gradient in income is highly suggestive of underlying biophysical drivers, of which disease conditions are an especially salient example. However, conclusions have been confounded by the simultaneous causality between income and disease, in addition to potentially spurious relationships. We use a simultaneous equations model to estimate the relative effects of vector-borne and parasitic diseases (VBPDs) and income on each other, controlling for other factors. Our statistical model indicates that VBPDs have systematically affected economic development, evident in contemporary levels of per capita income. The burden of VBDPs is, in turn, determined by underlying ecological conditions. In particular, the model predicts it to rise as biodiversity falls. Through these positive effects on human health, the model thus identifies measurable economic benefits of biodiversity.

While most of the world is thought to be growing economically, more than one-sixth of the world is roughly as poor today as their ancestors were hundreds of years ago. The extremely poor live largely in the tropics. This latitudinal gradient in income suggests that there are biophysical factors, such as the burden of disease, driving the effect. However, measuring the effects of disease on broad economic indicators is confounded by the fact that economic indicators simultaneously influence health. We get around this by using simultaneous equation modeling to estimate the relative effects of disease and income on each other while controlling for other factors. Our model indicates that vector-borne and parasitic diseases (VBPDs) have systematically affected economic development. Importantly, we show that the burden of VBPDs is, in turn, determined by underlying ecological conditions. In particular, the model predicts that the burden of disease will rise as biodiversity falls. The health benefits of biodiversity, therefore, potentially constitute an ecosystem service that can be quantified in terms of income generated.