Model-based risk assessment and public health analysis to prevent Lyme disease

Infectious Disease Sensitivity to Climate and Other Driver-Pressure Changes: Research Effort and Gaps for Lyme Disease and Cryptosporidiosis

Climate sensitivity of infectious diseases is discussed in many studies. A quantitative basis for distinguishing and predicting the disease impacts of climate and other environmental and anthropogenic driver-pressure changes, however, is often lacking. To assess research effort and identify possible key gaps that can guide further research, we here apply a scoping review approach to two widespread infectious diseases: Lyme disease (LD) as a vector-borne and cryptosporidiosis as a water-borne disease. Based on the emerging publication data, we further structure and quantitatively assess the driver-pressure foci and interlinkages considered in the published research so far. This shows important research gaps for the roles of rarely investigated water-related and socioeconomic factors for LD, and land-related factors for cryptosporidiosis. For both diseases, the interactions of host and parasite communities with climate and other driver-pressure factors are understudied, as are also important world regions relative to the disease geographies; in particular, Asia and Africa emerge as main geographic gaps for LD and cryptosporidiosis research, respectively. The scoping approach developed and gaps identified in this study should be useful for further assessment and guidance of research on infectious disease sensitivity to climate and other environmental and anthropogenic changes around the world.

A review of the effects of environmental hazards on humans, their remediation for sustainable development, and risk assessment

In the race for economic development and prosperity, our earth is becoming more polluted with each passing day. Technological advances in agriculture and rapid industrialization have drastically polluted the two pillars of natural resources, land and water. Toxic chemicals and microbial contaminants/agents created by natural and anthropogenic activities are rapidly becoming environmental hazards (EH) with increased potential to affect the natural environment and human health. This review has attempted to describe the various agents (chemical, biological, and physical) responsible for environmental contamination, remediation methods, and risk assessment techniques (RA). The main focus is on finding ways to mitigate the harmful effects of EHs through the simultaneous application of remediation methods and RA for sustainable development. It is recommended to apply the combination of different remediation methods using RA techniques to promote recycling and reuse of different resources for sustainable development. The report advocates for the development of site-specific, farmer-driven, sequential, and plant-based remediation strategies along with policy support for effective decontamination. This review also focuses on the fact that the lack of knowledge about environmental health is directly related to public health risks and, therefore, focuses on promoting awareness of effective ways to reduce anthropological burden and pollution and on providing valuable data that can be used in environmental monitoring assessments and lead to sustainable development.

An ecological approach to predict areas with established populations of Ixodes scapularis in Quebec, Canada

Public health management of Lyme disease (LD) is a dynamic challenge in Canada. Climate warming is driving the northward expansion of suitable habitat for the tick vector, Ixodes scapularis. Information about tick population establishment is used to inform the risk of LD but is challenged by sampling biases from surveillance data. Misclassifying areas as having no established tick population underestimates the LD risk classification. We used a logistic regression model at the municipal level to predict the probability of I. scapularis population establishment based on passive tick surveillance data during the period of 2010-2017 in southern Quebec. We tested for the effect of abiotic and biotic factors hypothesized to influence tick biology and ecology. Additional variables controlled for sampling biases in the passive surveillance data. In our final selected model, tick population establishment was positively associated with annual cumulative degree-days > 0°C, precipitation and deer density, and negatively associated with coniferous and mixed forest types. Sampling biases from passive tick surveillance were controlled for using municipal population size and public health instructions on tick submissions. The model performed well as indicated by an area under the curve (AUC) of 0.92, sensitivity of 86% and specificity of 81%. Our model enables prediction of I. scapularis population establishment in areas which lack data from passive tick surveillance and may improve the sensitivity of LD risk categorization in these areas. A more sensitive system of LD risk classification is important for increasing awareness and use of protective measures employed against ticks, and decreasing the morbidity associated with LD.

Cat Ownership and Rural Residence Are Associated with Lyme Disease Prevalence in the Northeastern United States

Lyme disease (LD) is the most common vector-borne disease in the USA. Beyond its tick-borne nature, however, risk factors for LD are poorly understood. We used an online questionnaire to compare LD patients and non-LD counterparts and elucidate factors associated with LD. We investigated demographic, lifestyle, and household characteristics and use of prevention measures. Associations with LD were modeled using logistic regression, and average marginal effects were estimated. In total, 185 active or past LD patients and 139 non-patients participated. The majority of respondents were white (95%) and female (65%). Controlling for age, sex, and type of residential area, pet ownership was associated with an 11.1% (p = 0.038) increase in the probability of LD. This effect was limited to cat owners (OR: 2.143, p = 0.007; dog owners, OR: 1.398, p = 0.221). Living in rural areas was associated with a 36% (p = 0.001) increase in the probability of LD compared to living in an urban area. Participants who reported knowing someone with Lyme Disease were more likely to wear insect repellant and perform tick checks. This study suggests opportunities for improved LD prevention, including advising cat owners of their increased risk. Although patterns in adoption of LD prevention methods remain poorly understood, concern about LD risk does motivate their use.

The evolving story of Borrelia burgdorferi sensu lato transmission in Europe

Beside mosquitoes, ticks are well-known vectors of different human pathogens. In the Northern Hemisphere, Lyme borreliosis (Eurasia, LB) or Lyme disease (North America, LD) is the most commonly occurring vector-borne infectious disease caused by bacteria of the genus Borrelia which are transmitted by hard ticks of the genus Ixodes. The reported incidence of LB in Europe is about 22.6 cases per 100,000 inhabitants annually with a broad range depending on the geographical area analyzed. However, the epidemiological data are largely incomplete, because LB is not notifiable in all European countries. Furthermore, not only differ reporting procedures between countries, there is also variation in case definitions and diagnostic procedures. Lyme borreliosis is caused by several species of the Borrelia (B.) burgdorferi sensu lato (s.l.) complex which are maintained in complex networks including ixodid ticks and different reservoir hosts. Vector and host influence each other and are affected by multiple factors including climate that have a major impact on their habitats and ecology. To classify factors that influence the risk of transmission of B. burgdorferi s.l. to their different vertebrate hosts as well as to humans, we briefly summarize the current knowledge about the pathogens including their astonishing ability to overcome various host immune responses, regarding the main vector in Europe Ixodes ricinus, and the disease caused by borreliae. The research shows, that a higher standardization of case definition, diagnostic procedures, and standardized, long-term surveillance systems across Europe is necessary to improve clinical and epidemiological data.

Analyzing the cost-effectiveness of Lyme disease risk reduction approaches

Lyme disease (LD) is endemic in many regions of the Northeastern United States. Given the elusive nature of the disease, a systematic approach to identify efficient interventions would be useful for policymakers in addressing LD. We used Markov modeling to investigate the efficiency of interventions. These interventions range from awareness-based to behavioral-based strategies. Targeting animal reservoirs of LD using fungal spray or bait boxes did not prove to be an effective intervention. Results of awareness-based interventions, including distribution of signage, fliers, and presentations, implementable in different geographical scales, suggest that policymakers should focus on these interventions, as they are both cost-effective and have the highest impact on lowering LD risk. Populations may lose focus of LD warnings over time, thus quick succession of these interventions is vital. Our modeling results identify the awareness-based intervention as the most cost-effective strategy to lower the number of LD cases. These results can aid in the establishment of effective LD risk reduction policy at various scales of implementation.

A system dynamics model of infection risk, expectations, and perceptions on antibiotic prescribing in the United States

RATIONALE, AIMS, AND OBJECTIVES

Inappropriate antibiotic prescribing is still a major concern that can lead to devastating outcomes including antibiotic resistance. This study aimed to simulate the antibiotic prescribing behaviour by providers for acute respiratory tract infections (ARTIs) and to evaluate the impact of patient expectation, provider's perception of patient's expectation to receive a prescription, and patient's risk for bacterial infection, on the decision to prescribe.

METHODS

We developed a unique system dynamics (SD) simulation model based on the significant factors that impact the interaction between provider and patient during visits for ARTIs and the decision to prescribe antibiotics. In order to validate the model for different age groups and regions in the United States, we used the sample of 53 000 ARTI patient visits made at outpatient settings between 1993 and 2015, based on the National Ambulatory Medical Care Survey (NAMCS).

RESULTS

Simulation results reveal that physician diagnosis for prescribing antibiotics is based on physician's experience from their prior prescribing behaviour, their perception of patient's infection risk, and patient's expectation to receive antibiotics. Also, there are some variations depending on patient's age and residential region. The simulation analysis also depicts the decreasing trend in patient's expectation over the past two decades for most age groups and regions.

CONCLUSIONS

Given the high number of unnecessary prescriptions for ARTI, we found that policies are needed to influence provider's prescribing behaviour through patient's expectation and provider's perception regarding those expectations. Our simulation framework can further be used by policymakers to design and evaluate interventions that may modify the interaction between health providers and patients to optimize antibiotic prescriptions among ARTI patients for different regions and age groups.

Comparing the Climatic and Landscape Risk Factors for Lyme Disease Cases in the Upper Midwest and Northeast United States

Lyme disease, recognized as one of the most important vector-borne diseases worldwide, has been increasing in incidence and spatial extend in United States. In the Northeast and Upper Midwest, Lyme disease is transmitted by Ixodes scapularis. Currently, many studies have been conducted to identify factors influencing Lyme disease risk in the Northeast, however, relatively few studies focused on the Upper Midwest. In this study, we explored and compared the climatic and landscape factors that shape the spatial patterns of human Lyme cases in these two regions, using the generalized linear mixed models. Our results showed that climatic variables generally had opposite correlations with Lyme disease risk, while landscape factors usually had similar effects in these two regions. High precipitation and low temperature were correlated with high Lyme disease risk in the Upper Midwest, while with low Lyme disease risk in the Northeast. In both regions, size and fragmentation related factors of residential area showed positive correlations with Lyme disease risk. Deciduous forests and evergreen forests had opposite effects on Lyme disease risk, but the effects were consistent between two regions. In general, this study provides new insight into understanding the differences of risk factors of human Lyme disease risk in these two regions.

Lyme Disease and the Epistemic Tensions of "Medically Unexplained Illnesses"

In the US, disagreement over the biological basis of "chronic Lyme disease" has resulted in the institutionalization of two standards of care: "mainstream" and "Lyme-literate." For mainstream physicians, chronic Lyme disease is a "medically unexplained illness" that presents with an abundance of "symptoms" in the absence of diagnostic "signs." For Lyme-literate physicians, and complementary and alternative medicine practitioners more generally, symptoms alone provide sufficient evidence for medical explanation. Drawing upon ethnographic research among mainstream and Lyme-literate physicians, I suggest that medically unexplained illness is not a biomedical anomaly but an intrinsic feature of biomedicine.

Risk Factors of Lyme Disease: An Intersection of Environmental Ecology and Systems Science

Lyme disease (LD) cases have been on the rise throughout the United States, costing the healthcare system up to $1.3 billion per year, and making LD one of the greatest threats to public health. Factors influencing the number of LD cases range from environmental to system-level variables, but little is known about the influence of vegetation (canopy, understory, and ground cover) and human behavioral risk on LD cases and exposure to infected ticks. We determined the influence of various risk factors on the risk of exposure to infected ticks on 22 different walkways using multinomial logistic regression. The model classifies the walkways into high-risk and low-risk categories with 90% accuracy, in which the understory, human risk, and number of rodents are significant indicators. These factors should be managed to control the risk of transmission of LD to humans.

Spatial dynamics of access to primary care for the medicaid population

Primary care (PC) has always been underestimated and underinvested by the United States health system. Our goal was to investigate the effect of Medicaid expansion and the Affordable Care Act (ACA) provisions on PC access in Broome County, NY, a county that includes both rural and urban areas, and can serve as a benchmark for other regions. We developed a spatial system dynamics model to capture different stages of PC access for the Medicaid population by using the health belief model constructs and simulate the effect of several hypothetical interventions on PC utilisation. The government data portals used as data sources for calibrating our model include the New York State Department of Health, the Medicaid Delivery System Reform Incentive Payment (DSRIP) dashboards, and the US census. In our unique approach, we integrated the simulation results within Geographical Information System (GIS) maps, to assess the influence of geospatial factors on PC access. Our results identify hot spot demographic areas that have poor access to PC service facilities due to transportation constraints and a shortage in PC providers. Our decision support tool informs policymakers about programmes with the strongest impact on improving access to care, considering spatial and temporal characteristics of a region.