Convergent trends and spatiotemporal patterns of Aedes-borne arboviruses in Mexico and Central America.

BACKGROUND: Aedes-borne arboviruses cause both seasonal epidemics and emerging outbreaks with a significant impact on global health. These viruses share mosquito vector species, often infecting the same host population within overlapping geographic regions. Thus, comparative analyses of the virus evolutionary and epidemiological dynamics across spatial and temporal scales could reveal convergent trends. METHODOLOGY/PRINCIPAL FINDINGS: Focusing on Mexico as a case study, we generated novel chikungunya and dengue (CHIKV, DENV-1 and DENV-2) virus genomes from an epidemiological surveillance-derived historical sample collection, and analysed them together with longitudinally-collected genome and epidemiological data from the Americas. Aedes-borne arboviruses endemically circulating within the country were found to be introduced multiple times from lineages predominantly sampled from the Caribbean and Central America. For CHIKV, at least thirteen introductions were inferred over a year, with six of these leading to persistent transmission chains. For both DENV-1 and DENV-2, at least seven introductions were inferred over a decade. CONCLUSIONS/SIGNIFICANCE: Our results suggest that CHIKV, DENV-1 and DENV-2 in Mexico share evolutionary and epidemiological trajectories. The southwest region of the country was determined to be the most likely location for viral introductions from abroad, with a subsequent spread into the Pacific coast towards the north of Mexico. Virus diffusion patterns observed across the country are likely driven by multiple factors, including mobility linked to human migration from Central towards North America. Considering Mexico's geographic positioning displaying a high human mobility across borders, our results prompt the need to better understand the role of anthropogenic factors in the transmission dynamics of Aedes-borne arboviruses, particularly linked to land-based human migration.

Aneurysms involving the coronary arteries in a neonate with neurofibromatosis 1.

Aneurysmal coronary artery disease (ACAD) has been reported rarely in patients with neurofibromatosis type 1 (NF1), mostly in adults. We report on a female newborn affected by NF1 with ACAD disclosed during investigation for an abnormal prenatal ultrasound along with a review of the previously reported cases. The proposita had multiple café-au-lait spots and had no cardiac symptoms. Echocardiography, and cardiac computed tomography angiography confirmed aneurysms on the left coronary artery, left anterior descending coronary artery, and of the sinus of Valsalva. Molecular analysis detected the pathogenic variant NM_001042492.3(NF1):c.3943C>T (p.Gln1315*). Literature findings on ACAD in NF1 indicated that this mostly occurs in males, showing predilection for the development of aneurysms at the left anterior descending coronary artery, and manifesting predominantly as acute myocardial infarction, inclusively in teenagers, though it may be also asymptomatic as in our case. This report documents the first case of ACAD in a patient with NF1 diagnosed at birth, emphasizing that its early diagnosis is essential to prevent potential life-threatening events attributable directly to coronary lesions.

Precision recruitment for high-risk participants in a COVID-19 research study

Studies for developing diagnostics and treatments for infectious diseases usually require observing the onset of infection during the study period. However, when the infection base rate incidence is low, the cohort size required to measure an effect becomes large, and recruitment becomes costly and prolonged. We describe an approach for reducing recruiting time and resources in a COVID-19 study by targeting recruitment to high-risk individuals. Our approach is based on direct and longitudinal connection with research participants and computes individual risk scores from individually permissioned data about socioeconomic and behavioural data, in combination with predicted local prevalence data. When we used these scores to recruit a balanced cohort of participants for a COVID-19 detection study, we obtained a 4-7-fold greater COVID-19 infection incidence compared with similar real-world study cohorts.

Emergence and spread of the potential variant of interest (VOI) B.1.1.519 predominantly present in Mexico.

SARS-CoV-2 variants have emerged in late 2020 and there are at least three variants of concern (B.1.1.7, B.1.351, P1) reported by WHO. These variants have several substitutions in the Spike protein that affect receptor binding; they present increased transmissibility and may be associated with reduced vaccine effectiveness. In the present work, we are reporting the identification of a potential variant of interest harboring the mutations T478K, P681H, and T732A in the Spike protein, within the newly named lineage B.1.1.519, which rapidly outcompeted the preexisting variants in Mexico and has been the dominant virus in the country during the first trimester of 2021.

Genomic analysis of early SARS-CoV-2 strains introduced in Mexico

The COVID-19 pandemic has affected most countries in the world. Studying the evolution and transmission patterns in different countries is crucial to implement effective strategies for disease control and prevention. In this work, we present the full genome sequence for 17 SARS-CoV-2 isolates corresponding to the earliest sampled cases in Mexico. Global and local phylogenomics, coupled with mutational analysis, consistently revealed that these viral sequences are distributed within 2 known lineages, the SARS-CoV-2 lineage A/G, containing mostly sequences from North America, and the lineage B/S containing mainly sequences from Europe. Based on the exposure history of the cases and on the phylogenomic analysis, we characterized fourteen independent introduction events. Additionally, three cases with no travel history were identified. We found evidence that two of these cases represent local transmission cases occurring in Mexico during mid-March 2020, denoting the earliest events described in the country. Within this Mexican cluster, we also identified an H49Y amino acid change in the spike protein. This mutation is a homoplasy occurring independently through time and space, and may function as a molecular marker to follow on any further spread of these viral variants throughout the country. Our results depict the general picture of the SARS-CoV-2 variants introduced at the beginning of the outbreak in Mexico, setting the foundation for future surveillance efforts. This work is the result of the collaboration of five institutions into one research consortium: three public health institutes and two universities. From the beginning of this work, it was agreed that the experimental leader of each institution would share the first authorship. Those were the criteria followed to assign first co-first authorship in this manuscript. The order of the other authors was randomly assigned. IMPORTANCEUnderstanding the introduction, spread and establishment of SARS-CoV-2 within distinct human populations is crucial to implement effective control strategies as well as the evolution of the pandemics. In this work, we describe that the initial virus strains introduced in Mexico came from Europe and the United States and the virus was circulating locally in the country as early as mid-March. We also found evidence for early local transmission of strains having the mutation H49Y in the Spike protein, that could be further used as a molecular marker to follow viral spread within the country and the region.

Measuring COVID-19 and Influenza in the Real World via Person-Generated Health Data

BackgroundSince the beginning of the COVID-19 pandemic, data from smartphones and connected sensors have been used to better understand presentation and management outside the clinic walls. However, reports on the validity of such data are still sparse, especially when it comes to symptom progression and relevance of wearable sensors. ObjectiveTo understand the relevance of Person-Generated Health Data (PGHD) as a means for early detection, monitoring, and management of COVID-19 in everyday life. This type of data include quantifying prevalence and progression of symptoms from self-reports as well as changes in activity and physiological parameters continuously measured from wearable sensors, and contextualizing findings for COVID-19 patients with those from cohorts of flu patients. Design, Setting, and ParticipantsRetrospective digital cohort study of individuals with a self-reported positive SARS-CoV-2 or influenza test followed over the period 2019-12-02 to 2020-04-27. Three cohorts were derived: Patients who self-reported being diagnosed with flu prior to the SARS-CoV-2 pandemic (N=6270, of which 1226 also contributed sensor PGHD); Patients who reported being diagnosed with flu during the SARS-CoV-2 pandemic (N=426, of which 85 also shared sensor PGHD); and patients who reported being diagnosed with COVID-19 (N=230, of which sensor PGHD was available for 41). The cohorts were derived from a large-scale digital participatory surveillance study designed to track Influenza-like Illness (ILI) incidence and burden over time. ExposuresSelf-reported demographic data, comorbidities, and symptoms experienced during a diagnosed ILI episode, including SARS-CoV-2. Physiological and behavioral parameters measured daily from commercial wearable sensors, including Resting Heart Rate (RHR), total step count, and nightly sleep hours. Main Outcomes and MeasuresWe investigated the percentage of individuals experiencing symptoms of a given type (e.g. shortness of breath) across demographic groups and over time. We examined illness duration, and care seeking behavior, and how RHR, step count, and nightly sleep hours deviated from expected behavior on healthy days over the course of the infection episode. ResultsSelf-reported symptoms of COVID-19 present differently from flu. COVID-19 cases tended to last longer than flu (median of 12 vs. 9 days), are uniquely characterized by chest pain/pressure, shortness of breath, and anosmia. The fraction of elevated RHR measurements collected daily from commercial wearable devices rise significantly in the 2 days surrounding ILI symptoms onset, but does not appear to do so in a way specific to COVID-19. Steps lost due to COVID-19 persists for longer than for flu. Conclusion and RelevancePGHD can be a valid source of longitudinal real world data to detect and monitor COVID-19-related symptoms and behaviors at population scale. PGHD may provide continuous, near real-time feedback to intervention effectiveness that otherwise requires waiting for symptoms to develop into contacts with the healthcare system. It has also the potential to increase pre-test probability of other downstream diagnostics. To effectively leverage PGHD for participatory surveillance it is crucial to invest in the creation of trusted, long-term communication channels with individuals through which data can be efficiently collected, consented, and contextualized, while protecting the privacy of individuals and ultimately facilitating the transition in and out of care.

Thermography mapping patterns in temporal lobe epilepsy surgery.

BACKGROUND: In several epilepsy etiologies, the macroscopic appearance of the epileptogenic tissue is identical to the normal, which makes it hard to balance between how much cytoreduction or disconnection and brain tissue preservation must be done. A strategy to tackle this situation is by evaluating brain metabolism during surgery using infrared thermography mapping (IrTM). METHODS: In 12 epilepsy surgery cases that involved the temporal lobe, we correlated the IrTM, electrocorticography, and neuropathology results. RESULTS: Irritative zones (IZ) had a lower temperature in comparison to the surrounding cortex with normal electric activity (difference in temperature (ΔT) from 1.2 to 7.1, mean 3.40°C standard deviation ± 1.61). The coldest zones correlated exactly with IZ in 9/10 cortical dysplasia (CD) cases. In case 3, the coldest area was at 1 cm away from the IZ. In 10/10 dysplasia cases (cases 1-4, 6-11), there was a radial heating pattern originating from the coldest cortical point. In 2/2 neoplasia cases, the temporal lobe cortical temperature was more homogeneous than in the CD cases, with no radial heating pattern, and there were no IZ detected. In case 8, we found the coldest IrTM recording in the hippocampus, which correlated to the maximal irritative activity recorded by strip electrodes. The ΔT is inversely proportional to epilepsy chronicity. CONCLUSION: IrTM could be useful in detecting hypothermic IZ in CD cases. As the ΔT is inversely proportional to epilepsy chronicity, this variable could affect the metabolic thermic patterns of the human brain.

The U.S.-Mexico Border Infectious Disease Surveillance project: establishing bi-national border surveillance.

In 1997, the Centers for Disease Control and Prevention, the Mexican Secretariat of Health, and border health officials began the development of the Border Infectious Disease Surveillance (BIDS) project, a surveillance system for infectious diseases along the U.S.-Mexico border. During a 3-year period, a binational team implemented an active, sentinel surveillance system for hepatitis and febrile exanthems at 13 clinical sites. The network developed surveillance protocols, trained nine surveillance coordinators, established serologic testing at four Mexican border laboratories, and created agreements for data sharing and notification of selected diseases and outbreaks. BIDS facilitated investigations of dengue fever in Texas-Tamaulipas and measles in California-Baja California. BIDS demonstrates that a binational effort with local, state, and federal participation can create a regional surveillance system that crosses an international border. Reducing administrative, infrastructure, and political barriers to cross-border public health collaboration will enhance the effectiveness of disease prevention projects such as BIDS.