Leveraging Technology to Manage Chagas Disease by Tracking Domestic and Sylvatic Animal Hosts as Sentinels: A Systematic Review

Mapping the Silent Threat: A Comprehensive Analysis of Chagas Disease Occurrence in Riverside Communities in the Western Amazon

Chagas disease (CD) is a typical tropical illness caused by Trypanosoma cruzi. The objective of this study was to assess the prevalence of Chagas disease in communities in two states of the Brazilian Amazon. Data collection occurred in July in the Alto Juruá region of Acre and in December in the communities of Humaitá, Amazonas, in 2019. A total of 477 participants were included in the study. In the communities of Alto Juruá, triatomine collections and analyses of T. cruzi infection were also carried out. All confirmed cases were found in the state of Acre, resulting in a total prevalence of 1.67. Of these eight cases, seven underwent ECG, all of which were concluded as normal by the physician team's cardiologists. Seventeen triatomine bugs, all belonging to the Rhodnius genus, were captured. The natural infection rate by T. cruzi was 25% in the Nova Cintra community and 66.67% in the Boca do Moa community (Alto Juruá). This research found that more than 1% of the studied population exhibited positive serological results for Chagas disease in the riverine communities during the study period, representing a small portion of cases among those who have not yet been diagnosed.

Profile of natural Trypanosoma cruzi infection among dogs from rural areas of southern Espírito Santo, Brazil

BACKGROUND

The emergence of Trypanosoma cruzi infection via oral transmission has a habitual character in its primitive endemic cycle. Recent findings revealed the first death by oral transmission of T. cruzi in the state of Espírito Santo, Brazil, in 2012, which was recorded in the rural area of Guarapari. This study evaluated the characteristics related to the occurrence of natural T. cruzi infection among dogs from the rural areas of Alegre and Iconha, municipalities of Espírito Santo.

METHODS

Logistic regression analysis of factors contributing to serological detection of T. cruzi in dogs was performed in environments where Espírito Santo's Department of Health Surveillance had previously notified triatomines positive for Trypanosoma spp. from 2014 to 2017.

RESULTS

A total of 36 dogs were analyzed, of which 10 (27.77%) tested positive, one was borderline (2.79%), and 25 tested negative (69.44%) for T. cruzi infection. São Caetano, a district from the Iconha municipality, presented a 25 times greater chance for the detection of positive tests (OR:25; 95% CI; 2.37->100). Dogs with updated mandatory vaccination presented with a lower risk of positive serodiagnosis (OR:0.12; 95% CI: 0.02-0.63).

CONCLUSIONS

Our results highlight for the first time the occurrence of natural T. cruzi canine infection, detected in the municipality of Iconha, mainly among dogs with un-updated mandatory vaccines in the district of São Caetano.

Early Warning Diagnostics for Emerging Infectious Diseases in Developing into Late-Stage Pandemics

The spread of infectious diseases due to travel and trade can be seen throughout history, whether from early settlers or traveling businessmen. Increased globalization has allowed infectious diseases to quickly spread to different parts of the world and cause widespread infection. Posthoc analysis of more recent outbreaks-SARS, MERS, swine flu, and COVID-19-has demonstrated that the causative viruses were circulating through populations for days or weeks before they were first detected, allowing disease to spread before quarantines, contact tracing, and travel restrictions could be implemented. Earlier detection of future novel pathogens could decrease the time before countermeasures are enacted. In this Account, we examined a variety of novel technologies from the past 10 years that may allow for earlier detection of infectious diseases. We have arranged these technologies chronologically from pre-human predictive technologies to population-level screening tools. The earliest detection methods utilize artificial intelligence to analyze factors such as climate variation and zoonotic spillover as well as specific species and geographies to identify where the infection risk is high. Artificial intelligence can also be used to monitor health records, social media, and various publicly available data to identify disease outbreaks faster than traditional epidemiology. Secondary to predictive measures is monitoring infection in specific sentinel animal species, where domestic animals or wildlife are indicators of potential disease hotspots. These hotspots inform public health officials about geographic areas where infection risk in humans is high. Further along the timeline, once the disease has begun to infect humans, wastewater epidemiology can be used for unbiased sampling of large populations. This method has already been shown to precede spikes in COVID-19 diagnoses by 1 to 2 weeks. As total infections increase in humans, bioaerosol sampling in high-traffic areas can be used for disease monitoring, such as within an airport. Finally, as disease spreads more quickly between humans, rapid diagnostic technologies such as lateral flow assays and nucleic acid amplification become very important. Minimally invasive point-of-care methods can allow for quick adoption and use within a population. These individual diagnostic methods then transfer to higher-throughput methods for more intensive population screening as an infection spreads. There are many promising early warning technologies being developed. However, no single technology listed herein will prevent every future outbreak. A combination of technologies from across our infection timeline would offer the most benefit in preventing future widespread disease outbreaks and pandemics.

Precision Health for Chagas Disease: Integrating Parasite and Host Factors to Predict Outcome of Infection and Response to Therapy

Chagas disease, caused by the infection with the protozoan parasite Trypanosoma cruzi, is clinically manifested in approximately one-third of infected people by inflammatory heart disease (cardiomyopathy) and, to a minor degree, gastrointestinal tract disorders (megaesophagus or megacolon). Chagas disease is a zoonosis transmitted among animals and people through the contact with triatomine bugs, which are found in much of the western hemisphere, including most countries of North, Central and South America, between parallels 45° north (Minneapolis, USA) and south (Chubut Province, Argentina). Despite much research on drug discovery for T. cruzi, there remain only two related agents in widespread use. Likewise, treatment is not always indicated due to the serious side effects of these drugs. On the other hand, the epidemiology and pathogenesis of Chagas disease are both highly complex, and much is known about both. However, it is still impossible to predict what will happen in an individual person infected with T. cruzi, because of the highly variability of parasite virulence and human susceptibility to infection, with no definitive molecular predictors of outcome from either side of the host-parasite equation. In this Minireview we briefly discuss the current state of T. cruzi infection and prognosis and look forward to the day when it will be possible to employ precision health to predict disease outcome and determine whether and when treatment of infection may be necessary.

Writing a Systematic Review for Publication in a Health-Related Degree Program

BACKGROUND

The protocol in this manuscript was designed to help graduate students publish. It is the result of a challenge from our provost in 2013. I developed this protocol over the last 6 years and have exercised the protocol for the last 5 years. The current version of the protocol has remained mostly static for the last 2 years-only small changes have been made to the process.

OBJECTIVE

The objective of this protocol is to enable students to learn a valuable skill of conducting a systematic review and to write the review in a way that can be published. I have designed the protocol to fit into the schedule of a traditional semester, but also used it in compressed semesters.

METHODS

An image map was created in HTML 5.0 and imported into a learning management system. It augments traditional instruction by providing references to published articles, examples, and previously recorded instructional videos. Students use the image map outside the classroom after traditional instruction. The image map helps students create manuscripts that follow established practice and are reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and whose authorship follows guidelines by the International Committee of Medical Journal Editors.

RESULTS

Since its inception, this protocol has helped 77 students publish 27 systematic reviews in nine journals worldwide. Some manuscripts take multiple years to progress through multiple review processes at multiple journals submitted in sequence. Two other professors in the School of Health Administration have used this protocol in their classes.

CONCLUSIONS

So far, this method has helped 51% of graduate students who used it in my graduate courses publish articles (with more manuscripts under consideration whose numbers have remained uncounted in this sum). I wish success to others who might use this protocol.