Surveillance Infrastructure Research Articles

TREVOR PAGLEN’S BORDER ABSTRACTIONS IN THE AGE OF MACHINE VISION

Over the past two decades, machine vision and artificial intelligence (AI) have become integrated into many aspects of daily life, and with machines generating images for other machines, humans are no longer at the centre of the image world. To explore the implications of the age of machine vision, this article focuses on a selection of work by American artist Trevor Paglen made between 2008 and 2018. It examines the significance of the US-Mexico border region as a site of his investigations and the role of abstraction in repositioning machine vision within the human-centred visual language of art. The article shows how Paglen’s body of work turns toward the nonhuman to consider what it means to make images when representation is no longer primarily a site for the construction of meaning by humans but is also a field of data for analysis by machines. It explores how Paglen conveys the interplay between different models of vision with an aesthetic sensibility that develops from the history of photography but signals the breakdown of representational photography. His work highlights the contested space of the US-Mexico border region as a key site in a surveillance infrastructure that depends on a new regime of vision and offers a space to reflect on what it means to live in a world where most images are now made by and for machines.

A fuzzy inference system for predicting outbreaks in emerging infectious diseases

The world population is vulnerable to emerging and possibly re-emerging infectious diseases. Climate change, globalization, increased travelling, and urbanization are dynamic factors behind disease emergence and reemergence. This study formulates and analyzes a model with five inputs, viz. Change of Landscape (CoL), Gateway of Travel (GoT), Hygiene, Sanitization, Housing (HSH), Health Infrastructure (HI), and Regularity of Surveillance (RoS) and one output, viz. Possibility of Outbreak to determine the effect of these variables on disease emergence using a Mamdani fuzzy inference system. We study the impact of these factors on disease emergence and the possibility of an outbreak in a particular region.

CARgram: CNN-based accident recognition from road sounds through intensity-projected spectrogram analysis

Road surveillance systems play an important role in traffic monitoring and detecting hazardous events. In recent years, several artificial intelligence-based approaches have been proposed for this purpose, typically based on the analysis of the acquired video streams. However, occlusions, poor lighting conditions, and heterogeneity of the events may often reduce their effectiveness and reliability. To overcome the limitations mentioned, scientific and industrial research has therefore focused on integrating such solutions with audio recognition methods. By automatically identifying anomalous traffic sounds, e.g., car crashes and skids, they help reduce false positives and missed alarms. Following this trend, in this work, we propose an innovative pipeline for the analysis of intensity-projected audio spectrograms from streams of traffic sounds, which exploits both (i) a visual approach based on a custom, special-purpose Convolutional Neural Network for the identification of anomalous events on the sound signal; and, (ii) a novel multi-representational encoding of the input, which proved to significantly improve the recognition accuracy of the neural models. The validation results of the proposed pipeline on the public MIVIA dataset, with a 0.96% of false positive rate, showed to be the best performance against the state-of-the-art competitors. Notably, following such findings, a prototype implementation has been deployed on a real-world video surveillance infrastructure.

Hepatitis B Care Continuum Models-Data to Inform Public Health Action.

The application of a care continuum model (CCM) can identify gaps in diagnosis, care, and treatment of populations with a common condition, but challenges are inherent in developing a CCM for chronic hepatitis B. In contrast with treatment for HIV or hepatitis C, treatment is not indicated for all people with chronic hepatitis B, clinical endpoints are not clear for those receiving treatment, and those for whom treatment is not indicated remain at risk for complications. This topical review examines the data elements necessary to develop and apply chronic hepatitis B CCMs at the jurisdictional health department level. We conducted a nonsystematic review of US-based publications in Ovid MEDLINE (1946-present), Ovid Embase (1974-present), and Scopus (not date limited) databases, which yielded 724 publications for review. Jurisdictional health departments, if properly supported, could develop locale-specific focused CCMs using person-level chronic hepatitis B registries, updated longitudinally using electronic laboratory reporting data and case reporting data. These CCMs could be applied to identify disparities and improve rates in testing and access to care and treatment, which are necessary to reduce liver disease and chronic hepatitis B mortality. Investments in public health surveillance infrastructure, including substantial enhancements in electronic laboratory reporting and case reporting and the use of supplementary data sources, could enable jurisdictional health departments to develop modified CCMs for chronic hepatitis B that focus, at least initially, on "early" CCM steps, which emphasize optimization of hepatitis B diagnosis, linkage to care, and ongoing clinical follow-up of diagnosed people, all of which can lead to improved outcomes.

Early warning systems for malaria outbreaks in Thailand: an anomaly detection approach

BackgroundMalaria continues to pose a significant health threat. Rapid identification of malaria infections and the deployment of active surveillance tools are crucial for achieving malaria elimination in regions where malaria is endemic, such as certain areas of Thailand. In this study, an anomaly detection system is introduced as an early warning mechanism for potential malaria outbreaks in countries like Thailand.MethodsUnsupervised clustering-based, and time series-based anomaly detection algorithms are developed and compared to identify abnormal malaria activity in Thailand. Additionally, a user interface tailored for anomaly detection is designed, enabling the Thai malaria surveillance team to utilize these algorithms and visualize regions exhibiting unusual malaria patterns.ResultsNine distinct anomaly detection algorithms we developed. Their efficacy in pinpointing verified outbreaks was assessed using malaria case data from Thailand spanning 2012 to 2022. The historical average threshold-based anomaly detection method triggered three times fewer alerts, while correctly identifying the same number of verified outbreaks when compared to the current method used in Thailand. A limitation of this analysis is the small number of verified outbreaks; further consultation with the Division of Vector Borne Disease could help identify more verified outbreaks. The developed dashboard, designed specifically for anomaly detection, allows disease surveillance professionals to easily identify and visualize unusual malaria activity at a provincial level across Thailand.ConclusionAn enhanced early warning system is proposed to bolster malaria elimination efforts for countries with a similar malaria profile to Thailand. The developed anomaly detection algorithms, after thorough comparison, have been optimized for integration with the current malaria surveillance infrastructure. An anomaly detection dashboard for Thailand is built and supports early detection of abnormal malaria activity. In summary, the proposed early warning system enhances the identification process for provinces at risk of outbreaks and offers easy integration with Thailand’s established malaria surveillance framework.

INFRASTRUCTURES OF MANIPULATION

This panel presents research on web and information infrastructures used for manipulative purposes. In contrast to platform manipulation (Woolley & Howard, 2018; Benkler et al., 2018), where users such as bad actors seek to gamify and exploit the weaknesses of online social media platforms like Twitter and TikTok, the papers in the present panel describe studies where web or information infrastructures such as those involved in search and information retrieval are manipulated to alter or produce facts (rather than social commentary on facts). For example, studies have shown how infrastructures like Google Search are manipulated by conservative elites (Tripodi, 2022), how anonymous editors use Wikidata to revise the distribution of information related to political protest movements (Ford, 2022), and how administrators harness information schemas to improve the findability of their advertising content (Iliadis, 2022). In these areas and more, web and digital infrastructures are being manipulated to serve the interests of politically motivated actors (Acker, 2018; Acker & Donovan, 2019). Infrastructures typically refer to shared public services like sewers, telephone poles, and electricity. According to Bowker et al. (2010, p. 98), information infrastructure refers to “digital facilities and services usually associated with the internet.” Information infrastructures are thus enabling resources, in network form, whose key role is that of a distributor, but rather than goods or services, information infrastructures distribute “knowledge, culture, and practice” (Bowker et al., 2010, p. 114). Such structures do this through their development of ontologies or classification schemes that enable dividing the world into categories or, through their application to large data sets, by offering an enormous, open store of data that can be used by others for a variety of purposes, such as retrieving facts and sharing information. Recently, several scholars have elaborated on the political nature of such infrastructural processes of digitization and datafication, including in the domains of archiving and preservation (Thylstrup, 2018, 2022), governance and management (Flyverbom & Murray, 2018), metrics and sorting (Alaimo & Kallinikos, 2021), and the creation of global ontologies for things like web search (Iliadis et al., 2023) and surveillance services (Iliadis & Acker, 2022). Manipulation of social media content and messaging is likewise a major research area over the last several years owing to the prevalence of online misinformation and disinformation campaigns (Reagle, 2016; Paris, 2021; Culloty & Suiter, 2021), particularly those associated with electoral politics (Tucker & Persily, 2020) and health misinformation (Keselman et al., 2022). Yet, online manipulation is not a new phenomenon and has long been discussed as a feature of the web in the context of the history of trolling, abuse, and hate (Phillips, 2015, 2019). Manipulation is thus a multivalent concept and is found in several domains which share the notion that manipulation is related to the altering, editing, treating, controlling, and influencing of content and messages for the purpose of misleading individuals. Historically, though, less attention has focused on manipulation as it has been mobilized infrastructurally, particularly with respect to the information infrastructures that transmit content and messages. Infrastructures should be understood here in a broad sense as undergirding the communication structures that transmit messages and content. Such infrastructures can be found in computer science, news and journalism, government, policy, and other areas where messaging is organized using some form of schema, whether it be technical, linguistic, financial, or otherwise. The first paper uses interviews to highlight the “importance of abortion-related web search and whether or not that system has been manipulated by actors trying to prevent abortion access.” The paper “examines how people (users) search for information about abortion, how organizations (content providers) utilize search engine optimization to reach potential users, and how advertisers try to attract visitors.” The second paper uses autoethnography and process tracing with respect to “the AP African American Studies debacle in order to elucidate digitally mediated disinformation as a strategy for stoking moral panic and thereby gaining widespread public buy-in to the establishment of educational censorship infrastructure.” The third paper analyzes Palantir as a surveillance platform that shapes and is shaped by infrastructures of manipulation. The paper “provides a method for researching companies like Palantir and its surveillance infrastructures” through digital media archiving of “over 600+ documents which have been stored, cleaned, annotated, and uploaded into an online digital archive that will be publicly available for media researchers to study.” The fourth and final paper is “an ethnographic study of a single Wikipedia article and how it evolved over the course of a decade” in the context of political revolutons. The paper describes “a framework for understanding new methods of controlling facts in the context of automated knowledge products” and “the importance of semantic infrastructure to new methods of control and influence on Wikipedia and the wider knowledge infrastructures that are increasingly dependent on it.”

Enhancing Urban Safety: The Role of Object Detection in Smart City Surveillance Systems

Urban safety is a critical concern in the development and management of smart cities. This article explores the transformative role of object detection technology in enhancing surveillance systems within these urban environments. Object detection, a subset of computer vision, enables the automated identification and tracking of various objects, such as vehicles, pedestrians, and unusual activities, in real-time. By integrating advanced object detection algorithms with existing surveillance infrastructures, smart cities can significantly improve public safety and response times. This paper reviews the current state of object detection technologies, their applications in urban surveillance, and the benefits they offer, including increased situational awareness, crime prevention, and efficient emergency management. Additionally, the article discusses challenges and future directions for research and development in this field, emphasizing the importance of ethical considerations and data privacy in the deployment of these technologies. Through case studies and practical examples, we illustrate how object detection is reshaping urban safety and contributing to the creation of more secure and resilient smart cities.

Collecting Multi-country Retrospective Antimicrobial Consumption and Use Data: Challenges and Experience.

Excessive or inappropriate antimicrobial use contributes to antimicrobial resistance, emphasizing the need to monitor and document the types and quantities of antibiotics used. Thus, data on antimicrobial consumption (AMC) and antimicrobial usage (AMU) are key in informing and promoting judicious use. Our study, conducted during 2019-2023, as part of the CAPTURA project, aimed to understand the state of data availability and quality for AMC and AMU monitoring in Asia. In this article, we describe the challenges and opportunities faced and provide examples of AMU and AMC analysis. World Health Organization (WHO) and country-tailored methodologies and tools were applied to collect retrospective data from 2016 to 2019 in Bangladesh, Bhutan, Laos, Nepal, Pakistan, Papua New Guinea, Sri Lanka, and Timor-Leste. The primary indicator for national AMC was total level of consumption, expressed as total defined daily doses (DDD) per 1000 inhabitants per day for the year or period of data collected. For facility AMC and AMU, the primary indicator was total DDD per admissions per day for the year or period of data collected. Although many countries faced infrastructural challenges in data collection and storage, we managed to collect and analyze AMC data from 6 countries and AMU data from 5. The primary indicators, and additional findings, were visualized to facilitate dissemination and promote the development of action plans. Looking ahead, it is crucial that future initiatives empower each country to establish surveillance infrastructures tailored to their unique contexts, ensuring sustainable progress in the fight against antimicrobial resistance.

Correlation of wastewater surveillance data with traditional influenza surveillance measures in Cook County, Illinois, October 2022–April 2023

Influenza is a respiratory illness that can result in serious outcomes, particularly among persons who are immunocompromised, aged <5 years or aged >65 years. Traditional influenza surveillance approaches rely upon syndromic surveillance of emergency departments and public health reporting from clinicians and laboratories. Wastewater surveillance infrastructure developed to monitor SARS-CoV-2 is being used for influenza surveillance in the Chicago area. The goal was to evaluate timeliness and correlations between influenza virus detected through wastewater surveillance and traditional influenza surveillance measures to assess utility of wastewater surveillance for influenza at the county level. Specifically, we measured correlations between influenza virus gene copies in wastewater samples and 1) the number of intensive care unit admissions associated with a diagnosis of influenza, 2) the percentage emergency department (ED) visits for influenza-like-illness, and 3) the percentage of ED visits with influenza diagnosis at discharge22Note: Visits may represent individual patients more than once. in Cook County. Influenza concentrations in wastewater were strongly correlated with traditional influenza surveillance measures, particularly for catchment areas serving >100,000 residents. Wastewater indicators lagged traditional influenza surveillance measures by approximately one week when analyzed in cross-correlations. Although wastewater data lagged traditional influenza surveillance measures in this analysis, it can serve as a useful surveillance tool as a complement to syndromic surveillance; it is a form of influenza surveillance that does not rely on healthcare-seeking behavior or reporting by healthcare providers.

Detection of Behaviors of Risk exhibited by People with Dementia with Privacy Protecting Videos

AbstractBehavioural symptoms of dementia present a significant risk within long‐term care homes, resulting in difficulties supporting residents and monitoring their safety due to limited staffing resources. Existing video surveillance infrastructure can be used to monitor and automatically detect clinically important behaviours that can put the residents at risk. An anomaly detection approach can be used to detect behaviours of risk from videos due to their infrequent and diverse nature. However, most existing video anomaly detection approaches focus on appearance‐based features, which can put the privacy of a person at risk and is also susceptible to pixel‐based noise. In this study, we explored different privacy‐protecting approaches and present a conditional average neighbour score method to detect behaviours of risks in videos from a dementia care unit. The conditional average neighbour score method considers that behaviours of risk in people with dementia are sometimes momentary, but often they persist over time. In this study, we used semantic segmentation masks approach to protect participants’ privacy by obscuring them in the video. The privacy‐protecting inputs were used to train a customized spatio‐temporal convolutional autoencoder and identify behaviours of risk as anomalies. The video was collected on a dementia care unit and composed of approximately 21 hours of training data (normal activities) and 9 hours of test data (normal activities and behaviours of risk events). In comparison to RGB input (0.822), we obtained an equivalent area under the receiver operating characteristic curve (AUC ROC) performance of 0.823 for the segmentation mask‐based privacy‐protecting approach. Further, using the conditional average neighbour score method, we improved the AUCROC performance to 0.83 for the segmentation mask‐based privacy‐protecting approach. The results signify that it is possible to use surveillance videos from a dementia care unit to detect behaviours of risk as anomalies, and that privacy protecting methods work as well as methods using the raw videos. This research paves the way to improve the quality of life of residents and reduce injuries in residential care homes, while respecting their privacy.

Little Samaritan Brothers: Crowdsourcing Voter Surveillance

Abstract Voter surveillance for digital campaigning is perceived as enacted from above. Political parties are “all-seeing actors” combining access to the Voters’ Registry with digital tools to maximize voter turnout. At the same time, new forms of lateral surveillance emerge as citizens voluntarily participate in the data collection process to help political parties achieve their electoral goals. This article examines the reconfiguration of the concepts of crowdsourcing and political participation through the use of voter-surveillance applications. Theoretically, it explores how crowdsourced voter surveillance (CVS) builds on the emancipatory rhetoric of political participation and crowdsourcing while relying on social, technical, and political surveillance infrastructures. Empirically, it maps the information flows and knowledge hierarchies afforded by Elector, a CVS app used by the Likud party in the Israeli election of March 2020. The findings indicate that contrary to the logic of crowdsourcing as democratizing knowledge and participation, CVS cultivates controlled individuals and normalizes lateral surveillance as a ritualistic and desired form of political participation. The article therefore describes the type of political action that CVS constructs as Little Samaritan Brothers: citizens who collectively resign their rights and the rights of their peers for the party’s success.

SARS-CoV-2 genomics and impact on clinical care for COVID-19.

The emergence and worldwide spread of SARS-CoV-2 during the COVID-19 pandemic necessitated the adaptation and rapid deployment of viral WGS and analysis techniques that had been previously applied on a more limited basis to other viral pathogens, such as HIV and influenza viruses. The need for WGS was driven in part by the low mutation rate of SARS-CoV-2, which necessitated measuring variation along the entire genome sequence to effectively differentiate lineages and characterize viral evolution. Several WGS approaches designed to maximize throughput and accuracy were quickly adopted by surveillance labs around the world. These broad-based SARS-CoV-2 genomic sequencing efforts revealed ongoing evolution of the virus, highlighted by the successive emergence of new viral variants throughout the course of the pandemic. These genomic insights were instrumental in characterizing the effects of viral mutations on transmissibility, immune escape and viral tropism, which in turn helped guide public health policy, the use of monoclonal antibody therapeutics and vaccine development strategies. As the use of direct-acting antivirals for the treatment of COVID-19 became more widespread, the potential for emergence of antiviral resistance has driven ongoing efforts to delineate resistance mutations and to monitor global sequence databases for their emergence. Given the critical role of viral genomics in the international effort to combat the COVID-19 pandemic, coordinated efforts should be made to expand global genomic surveillance capacity and infrastructure towards the anticipation and prevention of future pandemics.

Prevalence and Associated Factors of Dengue Virus Circulation in the Rural Community, Handeni District in Tanga, Tanzania.

Dengue virus is among the most important re-emerging arbovirus that causes global public health attention. Dengue has historically been thought of as an urban disease that frequently occurs in rapidly urbanized settings. However, dengue has become more widespread in rural regions in recent years. Understanding the changing dengue epidemiology in different geographical settings is important for targeted intervention. In Tanzania, dengue fever is not frequently reported because of the poor surveillance infrastructure, underestimation, and a lack of consideration of dengue as a priority. Therefore, the true burden as well as the risk factors for increased transmission has not been fully ascertained, particularly in rural areas. A cross-sectional community-based study was conducted in June 2021, involving a total of 362 participants of all age groups. We investigated the prevalence of acute dengue infection, seroprevalence, and associated factors among the community in three villages of the rural Handeni district. The prevalence of acute dengue infection (based on PCR) was 2.2% (8/362). Dengue-specific IgM and IgG antibodies were detected in 3.3% (12/362) and 5.2% (19/362) of the participants, respectively. Adult participants who were having vegetation around their houses were more likely to be DENV seropositive (AOR = 2.4, CI = 1.88-4.18, p value = 0.05). Children living in houses with garbage pit around their households were less likely to be DENV seropositive (AOR = 0.13, CI = 0.03-0.56, p value <0.01). DENV continues to circulate in rural Tanzania, causes an alarming situation, and necessitates prompt public health action to enhance vector surveillance and control in rural communities.

The state of integrated disease surveillance in seven countries: a synthesis report

ObjectivesIntegrated disease surveillance (IDS) offers the potential for better use of surveillance data to guide responses to public health threats. However, the extent of IDS implementation worldwide is unknown. This study sought to understand how IDS is operationalized, identify implementation challenges and barriers, and identify opportunities for development. Study designSynthesis of qualitative studies undertaken in seven countries. MethodsThirty-four focus group discussions and 48 key informant interviews were undertaken in Pakistan, Mozambique, Malawi, Uganda, Sweden, Canada, and England, with data collection led by the respective national public health institutes. Data were thematically analysed using a conceptual framework that covered governance, system and structure, core functions, finance and resourcing requirements. Emerging themes were then synthesised across countries for comparisons. ResultsNone of the countries studied had fully integrated surveillance systems. Surveillance was often fragmented, and the conceptualization of integration varied. Barriers and facilitators identified included: 1) the need for clarity of purpose to guide integration activities; 2) challenges arising from unclear or shared ownership; 3) incompatibility of existing IT systems and surveillance infrastructure; 4) workforce and skills requirements; 5) legal environment to facilitate data sharing between agencies; and 6) resourcing to drive integration. In countries dependent on external funding, the focus on single diseases limited integration and created parallel systems. ConclusionsA plurality of surveillance systems exists globally with varying levels of maturity. While development of an international framework and standards are urgently needed to guide integration efforts, these must be tailored to country contexts and guided by their overarching purpose.

Wuchereria bancrofti infection is associated with progression to clinical visceral leishmaniasis in VL- endemic areas in Muzaffarpur, Bihar, India.

Co-endemicity of neglected tropical diseases (NTDs) necessitates that these diseases should be considered concomitantly to understand the relationship between pathology and to support disease management and control programs. The aims of the study were to assess the prevalence of filarial infection in asymptomatic Leishmania donovani infected individuals and the correlation of Wuchereria bancrofti infection with progression to clinical visceral leishmaniasis (VL) in Bihar, India. Within the Muzaffarpur-TMRC Health and Demographic Surveillance System (HDSS) area, a cohort of Leishmania seropositive (n = 476) or seronegative individuals (n = 1130) were sampled annually for three years for filarial infection and followed for progression to clinical VL. To corroborate the results from the cohort study, we also used a retrospective case-control study of 36 VL cases and 71 controls selected from a subset of the HDSS population to investigate the relationship between progression to clinical VL and the prevalence of filarial infection at baseline. Our findings suggest a higher probability of progression to clinical VL in individuals with a history of filarial infection: in both the cohort and case-control studies, progression to clinical VL was higher among filaria infected individuals (RR = 2.57, p = 0.056, and OR = 2.52, p = 0.046 respectively). This study describes that progression to clinical VL disease is associated with serological evidence of prior infection with W. bancrofti. The integration of disease programs for Leishmania and lymphatic filariasis extend beyond the relationship of sequential or co-infection with disease burden. To ensure elimination targets can be reached and sustained, we suggest areas of co-endemicity would benefit from overlapping vector control activities, health system networks and surveillance infrastructure.

How does the geography of surveillance affect collective action?

AbstractHow does residing in the proximity of surveillance infrastructure—i.e., checkpoints, the separation barrier, and military installations—affect support for cooperative and confrontational forms of collective action? Cooperative actions involve engagement with outgroups to advance the ingroup cause (e.g., negotiations, joint actions, and peace movements), whereas confrontational actions involve unilateral tactics to weaken the outgroup (e.g., boycott, armed resistance). In the context of West Bank and Jerusalem, we combine geo‐coded data on the surveillance infrastructure with a representative survey of the adult population from 49 communities (N = 1,000). Our multilevel analyses show that surveillance does not affect support for confrontational actions but instead decreases support for cooperative actions. Moreover, we identify a new, community‐level mechanism whereby surveillance undermines cooperative actions through weakening inclusive norms that challenge dominant us‐versus‐them perspectives. These effects are empirically robust to various individual‐ and community‐level controls, as well as to the potential of reverse causality and residential self‐selection. Our findings illustrate how cooperative voices and the fabric of social communities become the first casualties of exposure to surveillance. They also speak to the importance of considering structural factors, with broader implications for the socio‐psychological study of collective action.

Has Data Quality of an Antimicrobial Resistance Surveillance System in a Province of Nepal Improved between 2019 and 2022?

An operational research study was conducted in 2019 to assess the quality of data submitted by antimicrobial resistance (AMR) surveillance sites in the Bagmati Province of Nepal to the National Public Health Laboratory for Global Antimicrobial Resistance and Use Surveillance System (GLASS). Measures were implemented to enhance the quality of AMR surveillance by strengthening capacity, improving infrastructure, implementing data sharing guidelines, and supervision. The current study examined reports submitted by surveillance sites in the same province in 2022 to assess whether the data quality had improved since 2019. The availability of infrastructure at the sites was assessed. Of the nine surveillance sites in the province, seven submitted reports in 2022 versus five in 2019. Completeness in reporting improved significantly from 19% in 2019 to 100% in 2022 (p < 0.001). Timely reports were received from two sites in 2019 and only one site in 2022. Specimen-pathogen consistency in accordance with the GLASS guidelines for urine, feces, and genital swab specimens improved, with ≥90% consistency at all sites. Overall, the pathogen-antibacterial consistency improved significantly for each GLASS priority pathogen. The study highlights the importance of dedicated infrastructure and institutional arrangements for AMR surveillance. Similar assessments covering all provinces of the country can provide a more complete country-wide picture.

Global perspectives in orofacial cleft management and research.

Orofacial clefts (OFCs) refer to clefts of the lip and palate, a heterogeneous group of relatively common congenital conditions that can cause mortality and significant disability if untreated, and residual morbidity even when treated with multidisciplinary care. Contemporary challenges in the field include: lack of awareness of OFCs in remote, rural and impoverished populations; uncertainties due to lack of surveillance and data gathering infrastructure; inequitable access to care in some parts of the world; and lack of political will combined with lack of capacity to prioritise research.OFCs present clinically as either syndromic or non-syndromic, with the latter either being isolated or in conjunction with other malformations; however, many registries still do not differentiate between these fundamentally different entities and lump a spectrum of cleft types and sub-phenotypes together. This has implications for treatment, research and ultimately, quality improvement.This paper deals with the challenges in contemporary management in terms of care and the prospects and possibilities for primary prevention of non-syndromic clefts. In terms of management and optimal care, there are also challenges in the provision of multi-disciplinary treatment and management of the consequences of being born with OFCs, such as dental caries, malocclusion and psychosocial adjustment.

Fentanyl, heroin, and methamphetamine-based counterfeit pills sold at tourist-oriented pharmacies in Mexico: An ethnographic and drug checking study

BackgroundFentanyl- and methamphetamine-based counterfeit prescription drugs have driven escalating overdose death rates in the US, however their presence in Mexico has not been assessed. Our ethnographic team has conducted longitudinal research focused on illicit drug markets in Northern Mexico since 2018. In 2021–2022, study participants described the arrival of new, unusually potent tablets sold as ostensibly controlled substances, without a prescription, directly from pharmacies that cater to US tourists. AimsTo characterize the availability of counterfeit and authentic controlled substances at pharmacies in Northern Mexico available to English-speaking tourists without a prescription. MethodsWe employed an iterative, exploratory, mixed methods design. Longitudinal ethnographic data was used to characterize tourist-oriented micro-neighborhoods and guide the selection of n=40 pharmacies in n=4 cities in Northern Mexico. In each pharmacy, samples of “oxycodone”, “Xanax”, and “Adderall” were sought as single pills, during English-language encounters, after which detailed ethnographic accounts were recorded. We employed immunoassay-based testing strips to check each pill for the presence of fentanyls, benzodiazepines, amphetamines, and methamphetamines. We used Fourier-Transform Infrared Spectroscopy to further characterize drug contents. ResultsOf n=40 pharmacies, one or more of the requested controlled substances could be obtained with no prescription (as single pills or in bottles) at 28 (70.0%) and as single pills at 19 (47.5%). Counterfeit pills were obtained at 11 pharmacies (27.5%). Of n=45 samples sold as one-off controlled substances, 18 were counterfeit. 7 of 11 (63.6%) samples sold as “Adderall” contained methamphetamine, 8 of 27 (29.6%) samples sold as “Oxycodone” contained fentanyl, and 3 “Oxycodone” samples contained heroin. Pharmacies providing counterfeit drugs were uniformly located in tourist-serving micro-neighborhoods, and generally featured English-language advertisements for erectile dysfunction medications and “painkillers”. Pharmacy employees occasionally expressed concern about overdose risk and provided harm reduction guidance. DiscussionThe availability of fentanyl-, heroin-, and methamphetamine-based counterfeit medications in tourist-oriented independent pharmacies in Northern Mexico represents a public health risk, and occurs in the context of 1) the normalization of medical tourism as a response to rising unaffordability of healthcare in the US, 2) plummeting rates of opioid prescription in the US, affecting both chronic pain patients and the availability of legitimate pharmaceuticals on the unregulated market, 3) the rise of fentanyl-based counterfeit opioids as a key driver of the fourth, and deadliest-to-date, wave of the opioid crisis. It was not possible to distinguish counterfeit medications based on appearance of pills or geography of pharmacies, because identically-appearing authentic and counterfeit versions were often sold in close geographic proximity. Nevertheless, people who consume drugs may be more trusting of controlled substances purchased directly from pharmacies. Due to Mexico’s limited opioid overdose surveillance infrastructure, the current death rate from these substances remains unknown.

The Insecure Migrant

Abstract For many Hondurans fleeing poverty, political corruption, violent crime, and climate change-induced disasters and seeking settlement in the United States, insecurity is a lived condition throughout the non-linear migratory journey. Add to that an ever-expanding surveillance infrastructure and thickening of the securitized US–Mexico border, and the very act of leaving arguably becomes political in its assertion of the right to dignified life. In this article I examine how undocumented Honduran migrants living in New Orleans rationalize the levels of risk they have faced during their migration and residency in the city. By focusing on violence—potential and actual—from petty criminals, gangs, traffickers, and law enforcement, I argue for heightened attention to how insecurity is an ongoing, cumulative, and transnational process that migrants face in their search for the good life.