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The Use of Remotely Sensed Data in Modeling Cholera Amidst Climate Change

By Shaina Eagle, Global Disease Biology, ‘24

Introduction 

Over 300,000 people reported having cholera in 2020 [12]. This infectious disease is spread by water or seafood contaminated by the Vibrio cholerae bacteria. V. cholerae can survive in the open ocean within phytoplankton [5]. The bacteria also spreads into inland water sources such as rivers, getting into people’s drinking water. This spread of cholera is affected by climate variables such as precipitation, temperature, and oceanic conditions [1, 2, 5, 6, 7, 11, 13]. Climate patterns such as the El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) influence local weather patterns in coastal regions, causing more phytoplankton blooms [2, 11]. Climate change also disrupts water, sanitation, and hygiene (WASH) infrastructure, [4] creating favorable environmental conditions for V. cholerae to thrive [2]. As climate change causes fluctuations in weather patterns and coastal biology, researchers need a reliable method for tracking and predicting cholera. Early warning systems are key for health officials to be able to take proper preventative measures–from vaccine deployment campaigns to emergency clean water storage–to reduce the prevalence and fatality of cholera.

Satellites are one method to gather measurements of variables that affect the spread of cholera. Using electromagnetic reflection, satellites provide remotely-sensed geophysical data on variables such as temperature, water quality, precipitation, or vegetation [10]. Researchers use remotely sensed data in conjunction with algorithms and statistical analyses to model cholera outbreaks and predict how changing variables will alter disease spread. Satellite data is widely accessible, often free, and provides data over huge temporal-spatial ranges [5, 10]. Researchers are able to compile their data without being physically near the areas they are studying [10]. This review will analyze how researchers have developed methods for predicting cholera outbreaks using remotely sensed data, and demonstrate how refinement of these techniques will be crucial to combating cholera outbreaks amidst climate change. 

Collection of Satellite Data

Natural disasters are increasing in intensity and frequency, heightening the opportunity for a cholera epidemic [2, 4]. Cholera epidemics have historically begun after storms, such as after Hurricane Matthew in Haiti [4]. Hurricanes can destroy WASH infrastructure, allowing cholera to seep into water supplies and leave people vulnerable to drinking this contaminated water [4]. Detecting outbreaks and identifying the source are crucial steps in managing deaths from cholera; it is also crucial to improve sanitation and access to clean drinking water and increase vaccination campaigns. These steps can be aided by remotely sensed data that feeds into prediction models [2].

Remotely sensed data measures variables that are known to be connected to cholera incidence. Huq et al. (2017) published research using remotely sensed precipitation, wind swath, geophysical landmarks, and population density after Hurricane Matthew struck Haiti in October 2016 [4]. The researchers created a map that showed areas at high risk for cholera and were able to predict where outbreak hotspots would occur up to four weeks after the hurricane [4].

Other useful variables include sea surface temperature (SST), sea surface salinity (SSS), land surface temperature (LST), precipitation, chlorophyll-a concentration (Ch-a), and soil moisture (SM) [1, 4, 5, 6, 7, 9, 11, 13]. SST and Ch-a are indicators of a habitat that is suitable for Vibrio cholerae growth [5, 6]. Flooding from extreme precipitation can flush seawater carrying V. cholerae into inland rivers, estuaries, or drinking water [4, 5, 6]. 

Satellites can provide data on climate variables in regions that health officials cannot access safely, or after a natural disaster when researchers cannot collect field data due to accessibility or time constraints [4]. This data could help researchers identify particular regions at risk for a cholera outbreak after an extreme weather event and help policymakers make informed decisions about where to implement vaccination programs or establish WASH infrastructure. And in districts where cholera survives endemically, remotely sensed data could help identify outbreak sources or thresholds for when an outbreak becomes an epidemic. Satellite data on EVCs and WASH infrastructure needs to remain publicly and freely available, and will be particularly effective in identifying potential cholera outbreaks as climate change increases the intensity and incidence of natural disasters and climate patterns that suit V. cholerae proliferation.

Turning Raw Data into Models

Tracking Essential Climate Variables

Satellites provide data across vast geospatial and temporal ranges about the Essential Climate Variables (ECVs) correlated with cholera outbreaks. Remote sensing systems allow researchers to build models of cholera dynamics based on these relationships [5]. Fooladi et al. (2021) used precipitation data from 1983 to 2016 to compute a non-standardized precipitation index (nSPI) in the Gavkhooni basin in Iran. Their model demonstrates how previous understanding of the environmental conditions that precede cholera outbreaks can be combined with satellite data to make novel predictions about disease outbreaks [3]. For example, an algal bloom is an exponential growth of phytoplankton, which requires chlorophyll-a to photosynthesize sunlight, grow, and produce nutrients [5]. Phytoplankton is a reservoir of V. cholerae and can be seen from space because of its green pigment. Therefore, Ch-a is a close enough proxy to phytoplankton for modeling the levels of V. cholerae bacteria in an area [5]. In 2021, Lai et al. used Landsat images from NASA and Sentinel-2A images from the European Space Agency to measure Ch-a in the Guanting Reservoir, one of the main water supply sources for Beijing, China. They developed a model between variables in the satellite images (bands, normalized difference vegetation index, surface algal bloom index, Apple algorithm values) and Ch-a [8]. Their studies in 2016, 2017, and 2019 predicted Ch-a to be correlated with the actual measured chlorophyll-a levels at a 0.05 significance level [8]. This data allowed the researchers to model trends of Ch-a and water nutrition status, which has applications to reservoir eutrophication statuses [8] and thus disease transmission.

Machine Learning

Variables such as LST and SM can be linked to cholera outbreaks through machine learning (ML) algorithms. ML elucidates complex relationships between variables, such as the risk of a cholera outbreak and EVCs [1]. Statistically analyzing input data taken from satellites, ML allows researchers to build models that predict an output (i.e. an outbreak) [9]. Algorithms such as Random Forest (RF), XGBoost, K-Nearest Neighbors, and Linear Discriminant Analysis have been examined by researchers [1, 9]. Campbell et al. (2020) found RF to be the most effective classifier due to its superior performance in handling oversampled and imbalanced datasets, yielding a high true positive rate (probability that an actual trend is correctly predicted) of 89.5% when fitting a model combining a season encoder, location encoder, LST, Ch-a, SSS, sea level anomalies, SM, and their lag values (using past variables to predict future variables) [1].  Campbell et al.’s model (2020) combined five EVCs and pulled data across forty districts of India from 2010 to 2018 [1]. 

In a 2013 study, Jutla acknowledged that Ch-a alone cannot serve as an accurate predictive factor of a cholera outbreak, as other organic matters and detritus not represented by a chlorophyll index can also contribute to the presence of cholera bacteria [6]. To account for this, Jutla developed the Satellite Water Marker (SWM) index, which uses wavelength radiance to identify coastal conditions and predict cholera outbreaks one to two months in advance [5]. SWM is based on the shifts in the difference between blue (412 nm) and green (555 nm) wavelengths, which determine the turbidity (impurity) of water [5]. A high correlation between SWM in the early winter months in the Bay of Bengal and cholera peaks in the spring was observed, and likely related to multiple coastal conditions, not just Ch-a [5]. Jutla et al. (2013) tested the Bay of Bengal SWM in Mozambique, where there is one annual cholera peak as opposed to two. They again found that the SWM was a more accurate indicator of cholera than Ch-a alone. Julta’s index was used again by Ogata et al. (2021) to determine the specific environmental conditions in previous seasons that precede cholera outbreaks in northern coastal regions in the Bay of Bengal. They linked spring cholera to summer precipitation and the previous fall/winter SWM. Meanwhile, La Niña-driven SST deviations and floods caused by high summer rainfall anticipated fall cholera outbreaks [11]. Variability in climate conditions and SWM over decades indicates that the predictive models are ever-shifting [11]. A clear understanding of shifts in climate patterns over time is thus integral to accurate forecasting.

Challenges and Limitations

Remotely sensed data is integral to developing timely and accurate predictive models and early warning systems for cholera outbreaks. There is no set of ECVs or a specific ML technique that can be applied universally, especially when looking at endemic versus epidemic cholera [1, 2, 5, 6, 7, 9]. Many studies struggled with a lack of field data against which to test their models, particularly after extreme weather events which may destroy existing data collection infrastructure [7]. Researchers were also challenged by imbalanced datasets when programming ML algorithms, even with particularly resilient algorithms like RF [1, 9].  Cholera is notoriously difficult to model because it can occur through multiple pathways of transmission, and cholera outbreaks are related to several climate variables through complex relationships [5, 6, 9]. Further testing in diverse regions, under various climate conditions, utilizing assorted ECVs, and employing numerous ML techniques is necessary to make these models as accurate as possible. Future studies should focus on long-term observations of variables known to be connected to cholera and V. cholerae, such as sea surface salinity [1, 11]. Future models also need to take socioeconomic data into account [1, 4].

Conclusion

The purpose of this review was to demonstrate how and why remotely sensed data is being used to predict cholera outbreaks, particularly as climate change makes local weather patterns more unpredictable. Researchers do not indicate a lack of sufficient satellite or ML technology necessary to make satellite data-driven cholera prediction models commonplace. However, different regions around the world have different seasonal and interannual variability of cholera transmission [5], making it difficult to develop a universal model. Therefore, future studies should emphasize testing various ML methods with diverse EVCs worldwide. Future studies should also work to formulate indices such as the SWM that can be applied over different geographical regions with minimal alterations. As climate change intensifies, cholera prediction models are vital components of disease prevention. Cholera is unlikely to be eradicated [5], but there are steps that can be taken to control its transmission and minimize its mortality. These steps are more effective the more time officials have to deploy them, so models that can provide significant lead times are critical.

Works Cited

[1] Campbell AM, Racault M-F, Goult S, Laurenson A. 2020. Cholera risk: a machine learning approach applied to essential climate variables. IJERPH. 17(24):9378.

[2] Christaki E, Dimitriou P, Pantavou K, Nikolopoulos GK. 2020. The impact of climate change on cholera: A review on the global status and future challenges. Atmosphere. 11(5):449.

[3] Fooladi M, Golmohammadi MH, Safavi HR, Singh VP. 2021. Fusion-based framework for meteorological drought modeling using remotely sensed datasets under climate change scenarios: resilience, vulnerability, and frequency analysis. Journal of Environmental Management. 297:113283.

[4] Huq A, Anwar R, Colwell R, McDonald MD, Khan R, Jutla A, Akanda S. 2017. Assessment of risk of cholera in Haiti following Hurricane Matthew. The American Journal of Tropical Medicine and Hygiene. 97(3):896–903.

[5] Jutla AS, Akanda AS, Islam S. 2010. Tracking cholera in coastal regions using satellite observations 1. JAWRA Journal of the American Water Resources Association. 46(4):651–662.

[6] Jutla A, Akanda AS, Huq A, Faruque ASG, Colwell R, Islam S. 2013. A water marker monitored by satellites to predict seasonal endemic cholera. Remote Sensing Letters. 4(8): 822-831.

[7] Khan R, Aldaach H, McDonald C, Alam M, Huq A, Gao Y, Akanda AS, Colwell R, Jutla A. 2019. Estimating cholera risk from an exploratory analysis of its association with satellite-derived land surface temperatures. International Journal of Remote Sensing. 40(13):4898–4909.

[8] Lai Y, Zhang J, Song Y, Gong Z. 2021. Retrieval and evaluation of chlorophyll-a concentration in reservoirs with main water supply function in Beijing, China, Based on Landsat Satellite Images. IJERPH. 18(9):4419.

[9] Leo J, Luhanga E, Michael K. 2019. Machine learning model for imbalanced cholera dataset in Tanzania. The Scientific World Journal. 2019:1–12.

[10] Moore GK. 1979. What is a picture worth? A history of remote sensing / Quelle est la valeur d’une image? Un tour d’horizon de télédétection. Hydrological Sciences Bulletin. 24(4):477–485.

[11] Ogata T, Racault M-F, Nonaka M, Behera S. 2021. Climate precursors of satellite water marker index for spring cholera outbreak in Northern Bay of Bengal coastal regions. International Journal of Environmental Research and Public Health. 18(19):10201.

[12] World Health Organization. 2021. Cholera annual report 2020. Weekly Epidemiological Record, Volume 96, page 445-460. 

[13] Xu M, Cao CX, Wang DC, Kan B, Xu YF, Ni XL, Zhu ZC. 2016. Environmental factor analysis of cholera in China using remote sensing and geographical information systems. Epidemiol Infect. 144(5):940–951.

Current threats to the Greater Everglades Ecosystem by invasive Burmese pythons

By Jessica Baggott, Evolution Ecology and Biodiversity Major, Professional Writing Minor, ’23

Author’s note: I wrote this piece in the Spring Quarter of 2022 for UWP 102B, Writing in the Disciplines: Biology. I wrote this piece partially because I have always fostered an interest in invasive species — how they enter, alter, and succeed in ecosystems. And, how we as scientists and policymakers address these threats to native ecosystems. I was also compelled to write this review because of the abundance of recent literature and the lack of another review, to my knowledge, that covered the same topics as I intended to.

I hope that readers walk away from this piece with a greater understanding of the Burmese python in the Florida Everglades — their invasion, success, and alterations to a fragile and precious ecosystem. I wish for readers to recognize the connections that I have made, combing through the literature, and I wish for them to make their own connections, too. There is no greater gift than your engagement with my work.

 

INTRODUCTION

Southern Florida’s Greater Everglades Ecosystem (GEE) once included over 8 million acres of 0.5-2.0 foot deep wetland from the Kissimmee Chain of Lakes just south of Orlando to the southern tip of Florida Bay [1]. Now, the GEE is estimated to be half of its historical size and is fragmented into various national, state, regional, and local parks as well as more than 12 wildlife refuges and marine preserves [2, 3, 4]. Everglades National Park (ENP), one of the federally protected regions of the GEE, only includes 1.5 million acres of this vast ecosystem [5]. However, even within the protected region of ENP, canals, pump stations, and roads have been  constructed to increase human accessibility to the Everglades, severely altering precise hydrological processes [1, 6]. These hydrological alterations, encroaching human settlements, degraded water quality, anthropogenic climate change, and the introduction of invasive species all pose significant threats to the GEE, and work in conjunction to increase negative effects on the GEE [4]. 

Perhaps the most infamous invasive species in the U.S., the Burmese python is the most well known threat to the GEE (Python molurus bivittatus). The snakes’ long lifespan, high fecundity or ability to produce offspring, as well as their generalist lifestyle which allows them to adapt their behavior and dietary habits to their environment, has allowed a small number of pythons to establish and thrive in the GEE [7]. Currently, Burmese pythons are drastically altering trophic structures as well as introducing and transmitting disease in the GEE. Furthermore, Burmese pythons have and have the potential to extend their range northward, putting other ecosystems and species at risk. A comprehensive literature review is required to inform policy decisions and assess the risk posed by Burmese pythons beyond the GEE.

Background

Native to Southeast Asia, the Burmese python was introduced into the GEE in the 1980s during a boom in the exotic pet trade and the subsequent release of the snakes into the Everglades by owners [7]. Since being first recognized in ENP in 2000, the invasive range of the Burmese python has rapidly expanded to the entirety of ENP and much of Big Cypress National Preserve [8]. However, population estimates have been hindered by the combination of cryptic python behavior (including long periods of inactivity), excellent natural camouflage, and human park management goals that include the removal of every python encountered without necessarily documenting the removed numbers [9]. These factors have caused extremely low python detection probabilities, ranging from 0.0001 to 0.0146 using visual surveys and radio transmitters [9]. Given low detection probability, population estimates range from tens of thousands to hundreds of thousands [9, 10]. Better population estimates are required for effective management strategies and to monitor changing populations of pythons [9].

Northward Range Expansion

Burmese pythons exhibit seasonal habitat preference, primarily choosing covered habitats close to water, though recent studies have found evidence that they may also be attracted to human development [11-17]. Smith et al. (2021) found that within their native range in Thailand, Burmese pythons do not avoid human dominated landscapes. Similarly, Bartoszek et al. (2021) found that in a northwest portion of ENP, within their invasive range, Burmese python hotspots were merely 515 meters from urban development on average. Researchers attributed this proximity to high quantities of readily available prey in these areas, in the form of livestock and birds attracted to the artificial lakes [11, 16]. However, egg clutches deposited in or near urban areas may exhibit lower survival rates than those in other habitats [8]. Though juveniles can travel long distances, particularly through use of agricultural canals, Pittman & Bartoszek (2021) hypothesize that in fact adult pythons with more sophisticated navigational capacities are the population driving expansion [18]. Adult sufficiency in and attraction to urban environments indicates that northward Burmese python expansion may not be hindered by human settlements. 

Besides suitable habitat, the range of ectotherms such as the Burmese python is typically limited by climate and/or the possession of behavioral adaptations such as retreating into underground refugia during winter months [19]. Though a conservative estimate allows Burmese pythons to survive for short periods of time at 5 °C,, temperatures must be above 16 °C in order for them to maintain digestion [19]. In isolation, these requirements make further expansion of the Burmese python in more northern parts of Florida extremely unlikely without the additional development of hibernation behaviors [19]. However, other researchers have found evidence of rapid adaptation for increased thermal tolerance after an extreme cold event in 2010 that caused high python mortality [20]. Adaptations included the maintenance of an active digestive system and changes in gene expression related to regenerative organ growth and behavior [20]. This rapid evolution by natural selection may permit Burmese pythons to expand their range northward into more temperate climates. 

However, there have been no studies in the last decade examining Burmese python’s potential for northward expansion, despite advances in climate and habitat models, tracking, and a greater understanding of Burmese python cold physiology. What studies do exist were inconclusive and results varied greatly: Rodda et al. (2009) and Pyron et al. (2008) provided oppositional potential range estimates. Rodda et al. (2009) concluded that the potential Burmese python range could include most of the southern U.S., from California through North Carolina. In contrast, Pyron et al. (2008) only included southern Florida and extreme southern Texas as the potential range of Burmese python expansion. Previous studies examining potential Burmese python range primarily agreed with Pyron et al. (2008) and all but two directly refuted the range suggested by Rodda et al. (2009) [19, 23-25]. Furthermore, climate change is projected to decrease the frequency and intensity of cold events in North America, allowing tropical species historically found at or near the equator, such as the Burmese python, to move poleward [26]. A literature review examining potential northward expansion of tropical organisms as a whole, with brief mentions of the Burmese python in Florida, posits that Burmese python range expansion is likely given the evidence for rapid adaptation for cold tolerance presented by Card et al. (2018) [26]. However, a complete understanding of the adaptive capacity of species, ecosystems, and biomes to climate change still remains lacking [26]. 

In addition to rapid adaptation to cold temperatures, Burmese pythons have shown evidence of hybridizing with another closely related invasive species, the Indian python (Python molurus) [27]. Hybridization has increased the population’s genetic diversity and allowed Burmese pythons to mitigate the founding and bottleneck effects — loss of genetic diversity due to a small founding population size or environmental effects [27]. Additionally, Hunter et al. (2018) found evidence of multiple paternity—the insemination of a female by more than one male during a single reproductive event—in Burmese pythons, also increasing python diversification rate. These behaviors allow for pythons to increase genetic diversity and will likely increase fitness, increasing the probability of northward expansion. 


Burmese Python Presence (1979–2016), Conyers & Sen Roy 2021.

Disease 

The invasion of the Burmese python in the GEE has introduced at least one pathogen, a lung parasite known as Raillietiella orientalis. Lacking coevolution with North American hosts, the spread and severity of this pathogen has increased in native species. This parasite now affects 13 species of native snakes and has extended beyond the python range into north central Alachua County, Florida, approximately 170 miles from the northernmost point of the GEE [28-30]. Researchers observed higher infection intensity, prevalence, and body size of R. orientalis in native snakes than in Burmese pythons, as native snakes do not share evolutionary history with R. orientalis and therefore are immunologically naive [29]. Infection by R. orientalis may be lethal or sublethal, and may be the cause of population decline of the pygmy rattlesnake [29, 31]. Additionally, R. orientalis’ native snake hosts have the highest rate of competence, or are most likely to transmit a resultant infection to a new host or vector after being exposed to a parasite. Furthermore, as R. orientalis’ native snake hosts are three of the most abundant snakes in North America [29], the parasite has a high likelihood of continued expansion throughout North America and possibly beyond [29]. Since the snakes of North America have not coevolved with R. orientalis, infections will be more severe and may cause population wide declines potentially resulting in devastating trophic cascades. The negative effects of the introduced parasite compound with those of Burmese python predation create weakened native populations more susceptible to parasitism, disease, and other stressors. More research is needed to ascertain the complete range of R. orientalis, expansion rate, intermediate hosts, sublethal effects on native snakes, and impact on populations. 

In addition to introducing a novel pathogen, Burmese pythons are competent hosts of at least one native pathogen and are suspected to be competent hosts of more [28, 32]. As a competent host to native pathogens, the Burmese python likely acts as a reservoir for these pathogens, and increases transmission to native species and humans [28, 32]. However, Burmese pythons are also able to change disease transmission through alteration of host communities via predation. Such is the case with the endemic Everglades Virus (EVEV), which can cause inflammation of the active tissues of the brain, known as clinical encephalitis, in humans. Decreased mammal diversity as a result of Burmese python predation was found to increase blood meals on amplifying hosts—hosts in which infectious agents multiply rapidly to high levels—increasing EVEV infection in mosquitoes [12]. Thus, it is possible that Burmese pythons could increase disease prevalence in humans as well, though contact with infected hosts is required for spread and therefore human disease may be driven by different factors than those in the mosquito-rodent cycle [12]. Understanding of the complex relationship between Burmese python predation on host species while also acting as hosts themselves remains lacking for many other important diseases, and presents an opportunity for future research. Additionally, studies should be conducted to estimate human risk as a result of the Burmese python altering host communities.

Further disease spillback is mediated by elevated rates of mosquito feedings on Burmese pythons [32]. The mosquitos that prefer feeding on Burmese Pythons also feed on a range of other species, including mammals, birds, reptiles, and amphibians [32]. Additionally, mosquito ranges extend beyond that of the Burmese python [32]. Thus, through both preferential feeding by mosquitoes on Burmese pythons and large mosquito range, the introduction of the Burmese python into the Everglades has increased disease spread beyond the python range.

Predation

The Burmese python has more than 40 prey documented in the Everglades, including a wide range of mammals and birds, and occasionally American alligators [33]. Given their appetite and potentially large population numbers, Burmese pythons are able to exert control over species populations. The decline of particular species relative to others can then cause ecosystem-wide cascades. Pythons have been found to cause severe mammal population declines through predation in their invasive range including 99.3%, 98.9%, and 87.5% decreases in observation frequency of raccoons, opossum, and bobcats respectively [33, 34]. Additionally, pythons have caused a complete local extinction of marsh rabbits, once one of the most commonly seen animals in ENP [33, 35, 36]. When reintroduced to ENP, marsh rabbits were able to establish a breeding population five months after translocation, but by 11 months after reintroduction, 77% of deaths were attributed to Burmese pythons and the population was unable to reestablish [35]. This disproportionate predation makes the reestablishment of this and other similarly affected species impossible as long as the python persists. Similarly, an analysis of anthropogenic stressors and those posed by pythons found that the strongest predictor for marsh rabbit occurrence was distance from the epicenter of python invasion [36]. These results indicate that pythons have profound effects on ecosystem composition through predation and are able to cause trophic cascades, damaging the ecosystem. Additionally, as is the case with Marsh Rabbits, species may be unable to reestablish in the core invasion area, even with translocation efforts. This demonstrates that without removal of Burmese pythons from the GEE, biodiversity and community composition of the GEE may be irreparably damaged.

Large, highly fecund species with wide habitat breaths were found to be the least susceptible to increased pressure from pythons, so the decline of a highly fecund and habitat generalist such as the marsh rabbit is especially concerning [37]. Using trait relationships, researchers predicted exclusively negative responses in occupancy probabilities to the presence of Burmese pythons regarding five unobserved species of concern: the everglades mink, feral hog, gray fox, red fox, and Key Largo woodrat [37]. Though rodent populations were previously thought to be resistant to the effects of pythons, declines in these populations have also been observed, and due to their lack of evolutionary history, one species, the Eastern woodrat, has even been suggested to be attracted to python scent [34, 38]. These results and research conducted on mammal resilience to pythons have shown that there is little evidence of resilience among mammals within the core invasion area, which only further contributes to the homogenization of the ecosystem [34]. Additionally, it is likely that loss of diversity and competition will allow other invasive species to establish more easily [34]. The results show the need for continued monitoring of species to analyze trends, research on response to novel predators, and the mechanisms for negative responses of native species to Burmese pythons. Furthermore, these results suggest that removal or significant population reduction of Burmese pythons may be the only way to curb their negative impacts. 

CONCLUSION

The purpose of this review was to examine the effects of the Burmese python in the GEE through predation, introduction and alteration of disease transmission, and potential range expansion. It is evident from this review that the Burmese python, through predation trophic alteration, has had severe effects on the native fauna of the GEE. Ultimately, it is the lack of coevolution between the Burmese python and native fauna that have led to the acute and persistent problems in the GEE. Burmese python establishment in the GEE has proved to be extremely detrimental to an ecosystem already facing considerable anthropogenic stressors. Given this, special attention should be paid to curb further Burmese python expansion to avoid similar ecological catastrophes due to the Burmese python. Further studies should be conducted regarding native resilience and recovery as populations eventually enter the third stage of invasion. Additionally, studies should be conducted to better quantify python density as to frame future understanding of ecosystem dynamics. The Burmese python is a prime example of many regarding invasive species across the globe. So, it is not only critical to better understand these aspects of python success and native fauna response, but the results may be applicable in the broader effort to manage invasive species. 

REFERENCES

  1. South Florida Water Management District. 2022. History of the Greater Everglades Ecosystem: Role of the Everglades in the Greater Everglades ecosystem.
  2. Office of Economic & Demographic Research. 2022. Annual Assessment of The Everglades. 5:1-19.
  3. Congressional Research Service. 2017. Everglades Restoration: Federal Funding and Implementation progress.
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Breast Cancer Screenings for Transgender Individuals

By Anisha Narsam, Neurobiology, Physiology, and Behavior, ’23

Author’s note: I hope to raise awareness about the barriers that transgender individuals face in order to obtain mammograms, and possible methods for increasing breast cancer screenings in this population. This article is meant for the general public and informs readers about some of the disparities that members of the LGBTQ community face, while also exploring methods that can be used to potentially bridge this gap in care. I chose this topic because I previously read an article about the disparities in cancer screenings in minority communities, and I wanted to research more about this topic specifically for transgender populations in relation to mammograms. Through this article, I hope readers can become more aware of how both transgender individuals and healthcare professionals lack knowledge on mammogram screening requirements, the barriers that can decrease mammogram rates, and methods that can improve breast cancer screening rates in transgender populations.

 

ABSTRACT

Objective: The aim is to analyze reasons for the gap in transgender breast cancer screenings, including the lack of proper screening guidelines and barriers to obtaining mammograms, and what can be done to alleviate this issue to improve healthcare for transgender individuals. 

Methods: This review analyzed primary research articles from the past three years from PubMed and Google Scholar. The sources were found with the key words “transgender breast cancer screening” and “transgender mammograms”, and were used to determine the extent of the disparity of breast cancer screenings for transgender individuals, existing knowledge of transgender mammogram requirements, barriers to obtain screenings, and methods to combat this issue. 

Results: Transgender individuals have decreased rates of breast cancer screenings compared to cisgender individuals due to healthcare workers’ lack of knowledge about transgender health and barriers for obtaining mammograms. Having more training for healthcare professionals, encouraging a more inclusive environment, and having organ inventories for patients to ensure all necessary screenings are met are a few ways to combat this issue and decrease disparities for transgender individuals to obtain these crucial mammograms. 

INTRODUCTION

Transgender individuals have disproportionately fewer mammograms than cisgender individuals [1]. According to the CDC, mammograms are pictures of the breast taken with an X-ray that physicians use to detect breast cancer [2]. By analyzing the current breast cancer screening rates of transgender individuals, understanding current knowledge of healthcare professionals on transgender health, addressing barriers that can prevent breast cancer screenings, and exploring ways to increase the number of mammograms transgender individuals obtain, this paper aims to encourage mammogram screenings to benefit transgender health [1, 3-11]. These studies are crucial for recognizing the barriers that prevent transgender individuals from getting mammograms, while also exploring the ways to counter such barriers to ensure the transgender population obtains these preventative screenings. Current research presents decreased breast cancer screening rates and lack of concrete breast cancer screening guidelines for transgender patients compared to cisgender patients [1, 9-11]. Moreover, research shows limited understanding of transgender health for healthcare workers [4-5]. One of the main barriers to obtaining mammograms is anxiety, including emotional and financial distress [3, 7, 11]. However, current research also presents potential solutions to the problem, including having more training for healthcare personnel, and having organ inventories for patients to understand each individual’s unique needs to help alleviate this issue by increasing the mammogram rates of transgender individuals [6, 8, 11]. This review focuses on current literature that provides information about access to breast cancer screenings for transgender individuals and how access can be improved.

DISCUSSION

Screening Rates and Knowledge on Screening Requirements

Transgender individuals have decreased rates of mammograms compared to cisgender individuals [1, 9-11]. Both a survey of transgender individuals from Iowa and a similar survey of transgender people from Dallas, Texas found that transgender men have lower breast cancer screening rates than cisgender females [1, 9]. However, there is variation in the percentage of transgender individuals obtaining mammograms in these different parts of the country. The Iowa study found that 75% of transgender men have obtained mammograms, a lower percentage than the 94% of cisgender women who have had mammograms [1]. On the other hand, the survey results from Texas indicate that only 40% of transgender males assigned female at birth have had mammograms at some point in their lives [9]. This demonstrates how there is variation across different parts of the country in regards to breast cancer screening rates for transgender men, although in both cases, rates are lower than that of cisgender individuals [1, 9]. These variations can be due to cultural differences in obtaining screenings, different state guidelines for screenings, or different socioeconomic statuses of individuals taking the survey that can affect whether or not they can afford their screenings [4, 11]. Moreover, researchers have also determined that rates of clinical breast exams, during which healthcare professionals use their hands to check for lumps in breast tissue, are even lower than the mammogram rates for transgender individuals [1, 12]. 

Transgender individuals also have limited knowledge of breast cancer screening requirements [9, 11]. In fact, according to researchers, over 65% of the sexual and gender minority community, which includes transgender individuals, is unaware of the screenings they require [11]. Other researchers confirm that there is a lack of knowledge in regards to the healthcare needs of transgender individuals, which translates to decreased knowledge in transgender populations themselves about the need for breast cancer screenings [8, 10]. Additionally, more than half of transgender individuals who were eligible for mammograms have not completed them which, according to researchers, demonstrates a limited understanding of organ-specific screening requirements [8]. Healthcare professionals also have limited knowledge on transgender mammogram requirements [4-5, 8].

Healthcare Professionals’ Existing Knowledge and Practices

Radiologists, genetic counselors, and healthcare staff have limited information about transgender breast cancer screening requirements and are less comfortable asking patients for their pronouns [4-5, 8]. In fact, 65% of radiologists did not recognize the importance of breast cancer screening guidelines for transgender men without chest surgery, and genetic counselors did not have the proper knowledge about the importance of breast cancer screenings for transgender women on estrogen therapy [4-5]. This demonstrates how more guidelines and protocols in relation to transgender mammograms need to be emphasized in healthcare environments [4, 11]. Both genetic counselors and radiologists agree that more research should be done to improve healthcare for transgender populations [4-5]. Genetic counselors reported in a survey feeling comfortable asking both transgender and cisgender patients about their pronouns [5]. Similarly, most radiologists claimed they felt comfortable asking patients about sex and gender identity for mammograms [4]. However, a survey of radiologists found that only 13% of physicians actually record both the sex and gender of transgender patients [4]. 

Also, in practice, when researchers observed providers and staff in another study, most healthcare professionals hesitated to ask the patient for their pronouns as they claimed they were uncomfortable and scared of offending the patient [8]. This demonstrates how although some healthcare professionals may claim to be comfortable asking about the gender and sex of patients, they may not execute this in practice, possibly because they are scared of offending the patient [4, 5, 8]. Transgender individuals may still develop breast cancer whether or not they identify with their biological sex, so it is imperative that healthcare providers ask for both gender and sex for each individual so they can obtain the preventative breast cancer screenings they require [3]. However, there can be many barriers to prevent access to such screenings [3, 7, 10-11].

Barriers and Inclusivity

Two of the main barriers for obtaining mammograms include anxiety or emotional distress associated with the appointment in transgender patients, as well as discrimination [3, 7, 10-11]. Transgender individuals have a disproportionately higher prevalence of anxiety. In an interview with one transgender individual, the patient stated that he was anxious about getting a breast cancer screening done because he did not want to stand out as the only man in a predominantly female division of the clinic, and this anxiety prevented him from getting screened [3, 7]. In fact, around half of transgender individuals do not get preventative cancer screenings because it causes them more emotional distress, on average, than these screenings do for cisgender individuals [11]. Such anxiety can also stem from the fear of being treated as their gender assigned at birth as opposed to the gender they identify as [7]. Another possible source of emotional distress comes from not having proper guidance on what screenings are recommended [4, 11].Although screening guidelines exist, there are no official nationwide screening recommendations published that can provide information on, for example, how having hormone therapy or gender-affirming surgeries can affect the types of screenings needed [4, 11]. Financial insecurities are a third source of emotional distress, with transgender individuals reporting lower incomes and health insurance coverage, causing around 50% of this population to postpone preventative cancer screenings as a result [3-4 10-11]. Moreover, transgender individuals experience higher rates of discrimination compared to cisgender groups, with around 52% of transgender individuals experiencing some type of discrimination, both during cancer screenings and for individuals who have received cancer treatment [3-4, 10]. Some examples of such discrimination include how 20% of transgender individuals were denied healthcare because they were gender-nonconforming, and how 20% of this population were also denied physician care for being transgender, which can lead to distrust in healthcare providers and a reduction in mammograms for transgender individuals [11].

Lack of inclusivity in medical settings can be another barrier for obtaining breast cancer screenings, and there can be contradicting information about what is considered inclusivity between transgender individuals and other outside populations, including researchers [3,7]. For example, based on a survey sent to radiology device companies, some of which provide the technology necessary for mammograms, researchers found that all responding companies had a third gender option of “other” when registering patients [3]. The only companies that responded were the ones that had more gender options than male and female, but the companies that did not respond may still have only two gender options [3]. Based on this information, researchers concluded that since there are more options than male and female on radiology devices, this demonstrates a more inclusive environment for transgender patients [3]. However, in an interview with one transgender individual, they mention how they feel offended when they are treated as the “other” just because they do not fit into any of the dominant gender groups, since it makes them feel alienated and unacknowledged [7]. This demonstrates how what may seem like positive language and inclusive language to some people can actually be alienating to transgender individuals in practice. Such language can, in fact, dissuade transgender individuals from obtaining mammograms, presenting another barrier to receiving the care they need [7,11]. It is crucial to combat such barriers to improve mammogram rates in transgender populations [3-4, 6-8, 11].

Methods to Improve Mammogram Rates

There are many methods that can be used to improve mammogram rates in transgender populations [3-4, 6-7, 11]. For example, training physicians and other hospital staff on methods for providing a more inclusive environment for transgender individuals can help patients feel more comfortable obtaining mammograms [3, 6, 11]. Also, providing more comfortable spaces, such as waiting rooms and changing rooms, at mammogram centers can help transgender patients feel more reassured and less anxious [11]. Another method to increase inclusivity is to have LGBTQ-specific mammogram services, or specific days the clinic is open just for LGBTQ individuals, so transgender patients would feel more reassured that the clinic is LGBTQ-friendly to ensure a more gender-affirming experience [7, 11]. It is also crucial for doctors and nurses themselves to be more understanding and listen to the patients’ concerns, since this can help build trust between the patient and provider [3, 11]. For example, one interviewed transgender patient mentioned that their physician not only affirmed their gender, but was also not forcing or chiding the patient into getting their previous gender-related preventative screenings, which made them feel a lot more comfortable and respected [7].  Once this trust is built, however, transgender patients are more likely to follow the physician’s screening recommendations, the physician provides, including for mammograms., to ensure transgender patients obtain the screenings they need [6, 9]. Physicians can also help build knowledge on mammograms for transgender individuals by enrolling their patients in a national research database that can consolidate  data about the screenings provided to patients and the outcomes of those screenings. Having this data can help healthcare professionals nationwide gain a more holistic view of the rates of certain cancers in the transgender populations, and what screenings should be emphasized for to transgender patients, as a result, to provide early detection for those specific cancers [4]. This can provide more holistic and concrete guidelines for mammograms to the entire country [4]. This database can present screening and outcome information of transgender individuals from around the country, providing a way to detect cancer rates and change how healthcare professionals treat patients based on the needs of the population [4]. Another way to ensure a more holistic understanding of each patient is to recommend organ-specific screenings, since each individual is unique, to ensure that patients do not miss any crucial cancer screenings, including mammograms [8]. In this way, healthcare professionals can ensure that no patient is left behind when it comes to obtaining such screenings. 

CONCLUSION

Overall, there are decreased amounts of breast cancer screenings done in transgender populations compared to cisgender populations, which is accompanied by a lack of knowledge of healthcare professionals on transgender screening requirements and barriers to screenings [1, 3-5, 7-11]. However, it has been shown that promoting doctor screening recommendations, having organ inventories, and providing a more supportive environment can positively combat this issue [3-4, 6-8, 11]. There are still more ways to improve screening rates by training healthcare providers and having a more inclusive environment, and further research needs to be done in this area to show the effects of such training on transgender mammogram screening rates [3, 6, 11]. Whereas some researchers argue that there is inclusivity in healthcare environments with radiology equipment having the third option for gender as “other”, transgender individuals themselves may not consider this language to be inclusive and it could instead make them feel sidelined in screening centers [3, 7]. Having more input from transgender individuals themselves on how they can be supported in breast cancer screening centers, and during the mammogram procedure, can increase comfort in healthcare environments to improve mammogram rates in this population [7]. 

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