Analysis of Social Determinants and the Utilization of Pediatric Tele-Urgent Care During the COVID-19 Pandemic: Cross-sectional Study.

BACKGROUND: Telehealth is increasingly used to provide specialty consultations to infants and children receiving care. However, there is uncertainty if the COVID-19 pandemic has influenced the use of telehealth among vulnerable populations. OBJECTIVE: This research aims to compare the overall use of tele-urgent care visits for pediatric patients before and after the pandemic, especially among vulnerable populations. METHODS: We conducted a cross-sectional analysis of pediatric tele-urgent care visits at a virtual care center at a southeastern health care center. The main outcome of this study was the use of pediatrics tele-urgent visits across geographical regions with different levels of social disparities and between 2019 and 2020. RESULTS: Of 584 tele-urgent care visits, 388 (66.4%) visits occurred in 2020 during the pandemic compared to 196 (33.6%) visits in 2019. Among 808 North Carolina zip codes, 181 (22%) consisted of a high concentration of vulnerable populations, where 17.7% (56/317) of the tele-urgent care visits originated from. The majority (215/317, 67.8%) of tele-urgent care visits originated from zip codes with a low concentration of vulnerable populations. There was a significant association between the rate of COVID-19 cases and the concentration level of social factors in a given Zip Code Tabulation Area. CONCLUSIONS: The use of tele-urgent care visits for pediatric care doubled during the COVID-19 pandemic. The majority of the tele-urgent care visits after COVID-19 originated from regions where there is a low presence of vulnerable populations. In addition, our geospatial analysis found that geographic regions with a high concentration of vulnerable populations had a significantly higher rate of COVID-19-confirmed cases and deaths compared to regions with a low concentration of vulnerable populations.

Accumulation, elimination, sequestration, and genetic variation of lead (Pb2+) loads within and between generations of Drosophila melanogaster.

We examined accumulation, sequestration, elimination, and genetic variation for lead (Pb) loads within and between generations of Drosophila melanogaster. Flies were reared in control or leaded medium at various doses and tested for their Pb loads at different stages of development (larvae, eclosion, newly-eclosed adults, and mature adults). Pb loads were tested using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). We found that D. melanogaster readily accumulated Pb throughout their lifespan and the levels of accumulation increased with Pb exposure in the medium. Wandering third-instar larvae accumulated more Pb than mature adults; this phenomenon may be due to elimination of Pb in the pupal cases during eclosion and/or depuration in adults post-eclosion. The accumulated Pb in mature adults was not transferred to F1 mature adult offspring. Using a set of recombinant inbred strains, we identified a quantitative trait locus for adult Pb loads and found that genetic variation accounted for 34% of the variance in Pb load. We concluded that D. melanogaster is a useful model organism for evaluating changes in Pb loads during development, as well as between generations. Furthermore, we found that genetic factors can influence Pb loads; this provides an essential foundation for evaluating phenotypic variation induced by the toxic effects of Pb.

Land Suitability Modeling using a Geographic Socio-Environmental Niche-Based Approach: A Case Study from Northeastern Thailand.

Understanding the pattern-process relations of land use/land cover change is an important area of research that provides key insights into human-environment interactions. The suitability or likelihood of occurrence of land use such as agricultural crop types across a human-managed landscape is a central consideration. Recent advances in niche-based, geographic species distribution modeling (SDM) offer a novel approach to understanding land suitability and land use decisions. SDM links species presence-location data with geospatial information and uses machine learning algorithms to develop non-linear and discontinuous species-environment relationships. Here, we apply the MaxEnt (Maximum Entropy) model for land suitability modeling by adapting niche theory to a human-managed landscape. In this article, we use data from an agricultural district in Northeastern Thailand as a case study for examining the relationships between the natural, built, and social environments and the likelihood of crop choice for the commonly grown crops that occur in the Nang Rong District - cassava, heavy rice, and jasmine rice, as well as an emerging crop, fruit trees. Our results indicate that while the natural environment (e.g., elevation and soils) is often the dominant factor in crop likelihood, the likelihood is also influenced by household characteristics, such as household assets and conditions of the neighborhood or built environment. Furthermore, the shape of the land use-environment curves illustrates the non-continuous and non-linear nature of these relationships. This approach demonstrates a novel method of understanding non-linear relationships between land and people. The article concludes with a proposed method for integrating the niche-based rules of land use allocation into a dynamic land use model that can address both allocation and quantity of agricultural crops.

Assessing the Application of a Geographic Presence-Only Model for Land Suitability Mapping.

Recent advances in ecological modeling have focused on novel methods for characterizing the environment that use presence-only data and machine-learning algorithms to predict the likelihood of species occurrence. These novel methods may have great potential for land suitability applications in the developing world where detailed land cover information is often unavailable or incomplete. This paper assesses the adaptation and application of the presence-only geographic species distribution model, MaxEnt, for agricultural crop suitability mapping in a rural Thailand where lowland paddy rice and upland field crops predominant. To assess this modeling approach, three independent crop presence datasets were used including a social-demographic survey of farm households, a remote sensing classification of land use/land cover, and ground control points, used for geodetic and thematic reference that vary in their geographic distribution and sample size. Disparate environmental data were integrated to characterize environmental settings across Nang Rong District, a region of approximately 1,300 sq. km in size. Results indicate that the MaxEnt model is capable of modeling crop suitability for upland and lowland crops, including rice varieties, although model results varied between datasets due to the high sensitivity of the model to the distribution of observed crop locations in geographic and environmental space. Accuracy assessments indicate that model outcomes were influenced by the sample size and the distribution of sample points in geographic and environmental space. The need for further research into accuracy assessments of presence-only models lacking true absence data is discussed. We conclude that the Maxent model can provide good estimates of crop suitability, but many areas need to be carefully scrutinized including geographic distribution of input data and assessment methods to ensure realistic modeling results.

A new method for detection of pfmdr1 mutations in Plasmodium falciparum DNA using real-time PCR.

BACKGROUND: Surveillance for drug-resistant Plasmodium falciparum should be a component of malaria control programmes. Real-time PCR methods for the detection of parasite single-nucleotide polymorphisms (SNPs) and gene amplification could be useful survellance tools. METHODS: A real-time PCR assay has been developed that identifies single nucleotide polymorphisms (SNPs) at amino acids 86, 184, 1034 and 1042 in the P. falciparum multi-drug resistant (pfmdr 1) gene that may be associated with anti-malarial drug resistance. RESULTS: This assay has a sensitivity and specificity of 94% and 100% when compared to traditional PCR methods for genotyping. Only 54 of 68 (79%) paired pre- and post-culture DNA samples were concordant at all four loci. CONCLUSION: Real-time PCR is a sensitive and specific method to detect SNP's in pfmdr 1. Genotypes of parasites after in vitro culture may not reflect that seen in vivo.