Control Measures Research Articles

Using image segmentation models to analyse high-resolution earth observation data: new tools to monitor disease risks in changing environments.

In the near future, the incidence of mosquito-borne diseases may expand to new sites due to changes in temperature and rainfall patterns caused by climate change. Therefore, there is a need to use recent technological advances to improve vector surveillance methodologies. Unoccupied Aerial Vehicles (UAVs), often called drones, have been used to collect high-resolution imagery to map detailed information on mosquito habitats and direct control measures to specific areas. Supervised classification approaches have been largely used to automatically detect vector habitats. However, manual data labelling for model training limits their use for rapid responses. Open-source foundation models such as the Meta AI Segment Anything Model (SAM) can facilitate the manual digitalization of high-resolution images. This pre-trained model can assist in extracting features of interest in a diverse range of images. Here, we evaluated the performance of SAM through the Samgeo package, a Python-based wrapper for geospatial data, as it has not been applied to analyse remote sensing images for epidemiological studies. We tested the identification of two land cover classes of interest: water bodies and human settlements, using different UAV acquired imagery across five malaria-endemic areas in Africa, South America, and Southeast Asia. We employed manually placed point prompts and text prompts associated with specific classes of interest to guide the image segmentation and assessed the performance in the different geographic contexts. An average Dice coefficient value of 0.67 was obtained for buildings segmentation and 0.73 for water bodies using point prompts. Regarding the use of text prompts, the highest Dice coefficient value reached 0.72 for buildings and 0.70 for water bodies. Nevertheless, the performance was closely dependent on each object, landscape characteristics and selected words, resulting in varying performance. Recent models such as SAM can potentially assist manual digitalization of imagery by vector control programs, quickly identifying key features when surveying an area of interest. However, accurate segmentation still requires user-provided manual prompts and corrections to obtain precise segmentation. Further evaluations are necessary, especially for applications in rural areas.

How to plan and provide general anesthesia for a troop of 98 hamadryas baboons (Papio hamadryas) for contraceptive and preventative health interventions.

Present an approach to the safe and efficient provision of anesthesia and birth control measures to a large group of primates. 98 hamadryas baboons (Papio hamadryas) held in a German zoological institution. A group of 12 veterinarians, 2 zookeepers, and 6 volunteers anesthetized all animals within 2 days. The baboons were orally premedicated with midazolam (0.1 to 0.5 mg/kg) and anesthetized with medetomidine (40 to 60 µg/kg, IM) and ketamine (2 to 4 mg/kg, IM); isoflurane at rates of 1.5% to 2% was used for maintaining anesthesia if necessary. All animals received a physical examination, prophylactic medication, and tuberculin testing. For population management, the animals received a contraceptive implant (adult females), orchiectomy (young males), or vasectomy (breeding males). Young males received intratesticular blocks with lidocaine. All animals received atipamezole (125 to 150 µg/kg) before recovery. Premedication resulted in anxiolysis, which facilitated separating and darting. Median time from darting to access to the animal was 10 minutes. Mean anesthetic times were 25 minutes for females and 55 minutes for males. The depth of anesthesia was appropriate for the procedures. No fatalities were recorded. One animal was injured by other baboons but recovered after treatment. Health management and birth control measures are necessary in baboon troops under human care. Anesthesia and/or contraception of individual animals often leads to intraspecific aggression. This case series describes how to provide anesthesia and contraception to an entire troop as an alternative approach that can be adopted to future similar interventions.

Real-life Achievements of MiniMed™ 780G Advanced Closed Loop System in Youth With Type 1 Diabetes: AWeSoMe Study Group Multi-Center Prospective Trial.

We assessed real-life glycemic outcomes and predictors of composite measures of optimal glycemic control in children and adolescents with type 1 diabetes (T1D) during their initial 12 months of the MiniMed™ 780G use. This prospective observational multicenter study collected demographic, clinical, and two-week 780G system data at five timepoints. Optimal glycemic control was defined as a composite glycemic control (CGC) score requiring the attainment of four recommended continuous glucose monitoring (CGM) targets, as well as the glycemia risk index (GRI) of hypoglycemia and hyperglycemia and composite CGM index (COGI). Outcome measures included longitudinal changes in multiple glycemic parameters and CGC, GRI, and COGI scores, as well as predictors of these optimal measures. The cohort included 93 children, 43% girls, with a median age of 15.1 years [IQR 12.9,17.0]. A longitudinal analysis adjusted for age and socioeconomic index yielded a significant improvement in glycemic control for the entire cohort (ptime<0.001) after the transition to 780G. The mean HbA1c (SE) was 8.65%(0.12) at baseline and dropped by more than 1% after one year to 7.54%(0.14) (ptime<0.001). Optimal glycemic control measures improved at 12 months post 780G; CGC improved by 5.6-fold (p<0.001) and was attained by 24% of the participants, the GRI score improved by 10-fold (p=0.009) and was achieved by 10% of them, and the COGI improved by 7.6-fold (p<0.001) and was attained by 20% of them. Lower baseline HbA1c levels and increased adherence to AHCL usage were predictors of achieving optimal glycemic control. The AHCL 780G system enhances glycemic control in children and adolescents with T1D, demonstrating improvements in HbA1c and CGM metrics, albeit most participants did not achieve optimal glycemic control. This highlights yet ongoing challenges in diabetes management, emphasizing the need for continued proactive efforts on the part of healthcare professionals, youth, and caregivers.

Encrypted data-sharing for preserving privacy in wastewater-based epidemiology.

The rapidly expanding use of wastewater for public health surveillance requires new strategies to protect privacy rights, while data are collected at increasingly discrete geospatial scales, i.e., city, neighborhood, campus, and building-level. Data collected at high geospatial resolution can inform on labile, short-lived biomarkers, thereby making wastewater-derived data both more actionable and more likely to cause privacy concerns and stigmatization of subpopulations. Additionally, data sharing restrictions among neighboring cities and communities can complicate efforts to balance public health protections with citizens' privacy. Here, we have created an encrypted framework that facilitates the sharing of sensitive population health data among entities that lack trust for one another (e.g., between adjacent municipalities with different governance of health monitoring and data sharing). We demonstrate the utility of this approach with two real-world cases. Our results show the feasibility of sharing encrypted data between two municipalities and a laboratory, while performing secure private computations for wastewater-based epidemiology (WBE) with high precision, fast speeds, and low data costs. This framework is amenable to other computations used by WBE researchers including population normalized mass loads, fecal indicator normalizations, and quality control measures. The Centers for Disease Control and Prevention's National Wastewater Surveillance System shows ~8 % of the records attributed to collection before the wastewater treatment plant, illustrating an opportunity to further expand currently limited community-level sampling and public health surveillance through security and responsible data-sharing as outlined here.

Rapid Management of Serratia marcescens Outbreak in Neonatology Unit in Singapore: Risk factors and Infection Control Measures.

To describe two consecutive Serratia marcescens outbreaks in neonatology unit of Singapore General hospital and determine risk factors associated with its acquisition in the second outbreak. Epidemiological investigations, environmental sampling and risk-factors analysis were used to guide infection control measures. Active surveillance sampling of nasopharyngeal aspirate and/or stool from neonates was conducted during both outbreaks. Whole-genome-sequencing was performed to determine clonal links. Retrospective case-control study was conducted in the second outbreak to identify risk factors for S. marcescens acquisition. In the one-year period in 2022, two S. marcescens outbreaks were managed involving five neonates in March 2022 outbreak and eight neonates in November 2022 outbreak. Both outbreaks were caused by genetically unrelated S. marcescens clones, with a link to positive isolates from sinks in intensive care units and milk preparation room during outbreak 1. Neonatal jaundice(OR, 16.46; p-value= 0.023) and non-formula milk feeding(OR, 13.88; p-value= 0.02) were identified as independent risk factors during second outbreak. Multiple interventions adopted were cohorting of positive cases, carriage-screening, enhanced environmental cleaning, and emphasis on alcohol-based handrubs for hand-hygiene. The two outbreaks in our institution were likely due to infection prevention practices lapses and favourable environmental conditions. Nosocomial S. marcescens outbreaks in neonatology units are difficult to control and require multidisciplinary approach with strict infection prevention measures to mitigate infection risks.

Review of current best practices for human milk banking.

Mother's/parent milk is the optimal way to feed infants and when unavailable, supplemental donor human milk is preferred. A safe supply of donor human milk should be available for all low birthweight infants for whom it has been shown to reduce morbidity. Human milk banking has been in existence for more than a century, although largely shut down during the 1980s, primarily due to fears of human immunodeficiency virus transmission. With renewed security in milk banking, has come an exponential growth in human donor milk use. Guidelines for milk banking have been published in many countries including Australia, France, India, Italy, Spain, Switzerland, the United Kingdom and the nonprofit organization PATH. The European Milk Bank Association and the Human Milk Banking Association of North America have also published recommendations for milk banks throughout Europe and North America, respectively. Although there is variability among these guidelines, there is general consensus on quality control measures required to provide a supply of safe donor milk. These measures include effective donor screening, safe collection, transport and storage of milk, standardized pasteurizationand bacteriological testing. Operational considerations are also critical, such as appropriate training for staff, equipment maintenance and cleaning, protocol and record keepingand inspection and accreditation. Clearly delineating these key quality control measures provides an excellent foundation for establishing international guidelines. Acceptable modifications must be established for low- and middle-income countries that do not have sufficient resources; overly burdensome guidelines may make establishing a milk bank unnecessarily prohibitive. This review presents a summary of current best practices for human milk banking.

Difference in Rumor Dissemination and Debunking Before and After the Relaxation of COVID-19 Prevention and Control Measures in China: Infodemiology Study.

The information epidemic emerged along with the COVID-19 pandemic. While controlling the spread of COVID-19, the secondary harm of epidemic rumors to social order cannot be ignored. The objective of this paper was to understand the characteristics of rumor dissemination before and after the pandemic and the corresponding rumor management and debunking mechanisms. This study aimed to provide a theoretical basis and effective methods for relevant departments to establish a sound mechanism for managing network rumors related to public health emergencies such as COVID-19. This study collected data sets of epidemic rumors before and after the relaxation of the epidemic prevention and control measures, focusing on large-scale network rumors. Starting from 3 dimensions of rumor content construction, rumor propagation, and rumor-refuting response, the epidemic rumors were subdivided into 7 categories, namely, involved subjects, communication content, emotional expression, communication channels, communication forms, rumor-refuting subjects, and verification sources. Based on this framework, content coding and statistical analysis of epidemic rumors were carried out. The study found that the rumor information was primarily directed at a clear target audience. The main themes of rumor dissemination were related to the public's immediate interests in the COVID-19 field, with significant differences in emotional expression and mostly negative emotions. Rumors mostly spread through social media interactions, community dissemination, and circle dissemination, with text content as the main form, but they lack factual evidence. The preferences of debunking subjects showed differences, and the frequent occurrence of rumors reflected the unsmooth channels of debunking. The χ2 test of data before and after the pandemic showed that the P value was less than .05, indicating that the difference in rumor content before and after the pandemic had statistical significance. This study's results showed that the themes of rumors during the pandemic are closely related to the immediate interests of the public, and the emotions of the public accelerate the spread of these rumors, which are mostly disseminated through social networks. Therefore, to more effectively prevent and control the spread of rumors during the pandemic and to enhance the capability to respond to public health crises, relevant authorities should strengthen communication with the public, conduct emotional risk assessments, and establish a joint mechanism for debunking rumors.

Delving a stochastic SEQAIJR COVID-19 model with hexa delayed and copious control strategies

The actual ideal of the literature is to probe the effect of external undulation on prevalence of COVID-19. Owing to some environmental influences, we enhanced our model to the stochastic perturbations. In this article, we scrutinize a stochastic epidemic COVID-19 model with seven states of epidemiological classification. Incipiently, a sophisticated biological system with the effect of time lags put forward copious strategies. At the outset, aim of this work is to explore the existence and uniqueness of global positive solution. Moment exponential stability are upheld. By fabricating a suitable lyapunov function, the sufficient conditions for the persistence of the disease and the existence of an ergodic stationary distribution are established. To regulate the widespread of COVID-19 infection, the main intent is to curb the disease with the succor of three control measures. Finally, the theoretical results bring into being alive in the form of graphical visualization. By nurturing the comparison study, the parameters of the model system come up with real data of most afflicted countries that layout premier consequences.

Sequencing analysis of SARS-CoV-2 cases in Slovenian long-term care facilities to support outbreak control

IntroductionResidents of long-term care facilities (LTCFs) are at high risk of morbidity and mortality due to COVID-19, especially when new variants of concern (VOC) emerge. To provide intradisciplinary data in order to tailor public health interventions during future epidemics, available epidemiologic and genomic data from Slovenian LTCFs during the initial phases of the COVID-19 pandemic was analyzed.MethodsThe first part of the study included SARS-CoV-2 reverse-transcription Real-Time PCR (rtRT-PCR) positive LTCF residents, from 21 facilities with COVID-19 outbreaks occurring in October 2020. The second part of the study included SARS-CoV-2 rtRT-PCR positive LTCF residents and staff between January and April 2021, when VOC Alpha emerged in Slovenia. Next-generation sequencing (NGS) was used to acquire SARS-CoV-2 genomes, and lineage determination. In-depth phylogenetic and mutational profile analysis were performed and coupled with available field epidemiological data to assess the dynamics of SARS-CoV-2 introduction and transmission.Results370/498 SARS-CoV-2 positive residents as well as 558/699 SARS-CoV-2 positive residents and 301/358 staff were successfully sequenced in the first and second part of the study, respectively. In October 2020, COVID-19 outbreaks in the 21 LTCFs were caused by intra-facility transmission as well as multiple independent SARS-CoV-2 introductions. The Alpha variant was confirmed in the first LTCF resident approximately 1.5 months after the first Alpha case was identified in Slovenia. The data also showed a slower replacement of existing variants by Alpha in residents compared to staff and the general population.DiscussionMultiple SARS CoV-2 introductions as well as intra-facility spreading impacted disease transmission in Slovenian LTCFs. Timely implementation of control measures aimed at limiting new introductions while controlling in-facility transmission are of paramount importance, especially as new VOCs emerge. Sequencing, in conjunction with epidemiological data, can facilitate the determination of the need for future improvements in control measures to protect LTCF residents from COVID-19 or other respiratory infections.

Climate-smart Pest Management Strategies: Under Changing Climatic Scenarios

In the face of changing climatic conditions, it's crucial to acknowledge their far-reaching impacts on humans, animals, and agricultural systems worldwide, where negative consequences often overshadow any positive outcomes. With global warming and climate change, previously minor insect pests are now poised to wreak havoc, leading to widespread pest outbreaks. As a result, the effectiveness of various pest control measures, including host-plant resistance, natural enemies, transgenics, bio-pesticides, and synthetic chemicals, may undergo significant shifts. Growers and researchers are actively devising Integrated Pest Management (IPM) strategies to minimize environmental harm while maximizing crop yields and economic benefits. Numerous studies highlight the necessity of reevaluating pest management practices and IPM strategies to adapt to novel environmental conditions and enhance the resilience of diverse agroecosystems to weather variability. This involves initiatives such as breeding climate-resilient crops, adjusting crop calendars, employing GIS-based risk mapping for crop pests, and exploring novel pesticides with alternative modes of action, informed by predictive modeling data. Thus, this chapter explores the potential of these techniques for climate-smart insect pest management.

SQEAIR: an Improved Infectious Disease Dynamics Model

The Covid-19 pandemic poses a significant threat to human health and life. Timely and accurate prediction of the epidemic’s trajectory is crucial for devising effective prevention and control strategies. Traditional infectious disease models may not capture the complexity of modern epidemics, especially when governments implement diverse policies. Drawing from China’s epidemic prevention strategies and Covid-19 transmission characteristics, this study introduces two distinct categories quarantined cases and asymptomatic cases to enhance the traditional SEIR model in depicting disease dynamics. To address the intricate nature of prevention and control efforts, the quarantined cases are further segmented into three subgroups: exposed quarantined, asymptomatic quarantined, and infected quarantined cases. Consequently, a novel SQEAIR model is proposed to model the dynamics of Covid-19. Evaluation metrics such as the Akaike information criterion (AIC) and Absolute Percentage Error (MAE) are employed to assess the efficacy and accuracy of both the newly proposed and traditional models. By fitting the models to the number of infected cases in Shanghai (March to May 2022) and Guangzhou (November 2022), it was observed that the SQEAIR model exhibited a lower AIC value compared to the SEIR model, indicating superior fitting accuracy for Covid-19 infections. Moreover, the high accuracy of the SQEAIR model enabled precise predictions of confirmed cases in Guangzhou. Leveraging the SQEAIR model, various parameters were tested to simulate the impact of different influencing factors, enabling the evaluation of defense strategies. These findings underscore the effectiveness of key epidemic control measures, such as quarantining exposed cases, in enhancing public health and promoting awareness of personal protection.

Genomic characterization of infectious bursal disease virus in Argentina provides evidence of the recent transcontinental spread of Chinese genotype A2dB1b

ABSTRACT The infectious bursal disease virus (IBDV) is a significant pathogen affecting the poultry industry worldwide. Its epidemiological history has been marked by the emergence of strains with different antigenic, pathogenic, and genetic features, some of which have shown notable spread potential. The A2dB1b genotype, also known as novel variant, has become widespread and gained increased relevance in IBDV epidemiology. This genotype was described in China in the 2010s and rapidly spread in Asia and Africa. The present study describes the circulation of the A2dB1b genotype in Argentina. Applying a next-generation sequencing approach, we obtained the complete coding sequence of 18 Argentine viruses. The high level of genomic homogeneity observed amongst these viruses, their monophyletic clustering in both partial and complete segments A and B derived phylogenies, and their close relatedness to some Chinese strains suggest that a unique transcontinental spread event from China to Argentina occurred recently. The apparent success of the A2dB1b genotype spreading throughout Asia, Africa, and South America may partially be due to specific amino acid characteristics. Novel residues in the hypervariable region of VP2 may help A2dB1b IBDVs evade the protection elicited by the applied commercial vaccines. Our findings underscore the importance of continuous characterization of field samples and evaluation of the control measures currently applied to struggle against this specific IBDV genotype.

Ecological construction status of photovoltaic power plants in China’s deserts

Solar photovoltaic (PV) is one of the most environmental-friendly and promising resources for achieving carbon peak and neutrality targets. Despite their ecological fragility, China’s vast desert regions have become the most promising areas for PV plant development due to their extensive land area and relatively low utilization value. Artificial ecological measures in the PV plants can reduce the environmental damage caused by the construction activity and promote the ecological condition of fragile desert ecosystems, therefore yield both ecological and economic benefits. However, the understanding of the current status and ecological benefits of this approach in existing desert PV plants is limited. Here we surveyed 40 PV plants in northern China’s deserts to identify the ecological construction modes and their influencing factors. We quantified the ecosystem service value (ESV) provided by these PV plants using remote sensing data and estimated the potential for ESV enhancement. Our results show that PV plant construction in desert regions can significantly improve the ecosystem, even with natural restoration measures (M1) alone, resulting in a 74% increase in average fractional vegetation cover (FVC) during the growing season, although the maximum average FVC of only about 10%. The integrated mode M4, which combined artificial vegetation planting M2 and sand control measures M3, further enhance the average growing season FVC to 14.53%. Currently, 22.5% of plants lack ecological measures, 40% employ only a single measure, but 92% of new plants since 2017 have adopted at least one ecological construction mode. The main influencing factors include surface type, policy support, water resources, ecological construction costs, and scientific management guidance. If artificial ecological construction were incorporated, a significant ESV could be achieved in these PV plants, reaching $8.9 million (a 7.7-fold increase) if assuming a targeted 50% vegetation coverage. This study provides evidence for evaluating the ecological benefit and planning of large-scale PV farms in deserts.

Spatial distribution and environmental correlations of Culex pipiens pallens (Diptera: Culicidae)in Haidian district, Beijing.

Culex pipiens pallens Coquillett, 1898(Diptera: Culicidae)was the dominant health threat to mosquito species in Beijing, and it is important to unravel the spatial distribution and environmental correlations of Cx. pipiens pallens in Beijing. 3S technology methods and spatial statistics were used to clarify the distribution pattern. Subsequently, linear and spatial regression were performed to detect the environmental factors linked with the density of Cx. pipiens pallens. The same "middle peak" spatial distribution pattern was observed for Cx. pipiens pallens density at the community, subdistrict, and loop area levels in our study area. In addition, there were various correlated environmental factors at the community and subdistrict scales. At the community scale, the summary values of the Modified Normalized Difference Water Index (MNDWI) in 2 km buffer zone (MNDWI_2K) were negatively correlated, and the summary values of Normalized Difference Built-up Index (NDBI) in 800 m buffer zone (NDBI_800) was positively correlated to the Cx. pipiens pallens density. However, the summary values of Normalized Difference Vegetation Index and Nighttime Light Index significantly affected Cx. pipiens pallens density at the subdistrict scale. Our findings provide insight into the spatial distribution pattern of Cx. pipiens pallens density and its associated environmental risk factors at different spatial scales in the Haidian district of Beijing for the first time. The results could be used to predict the Cx. pipiens pallens density as well as the risk of lymphatic filariasis (LF) infection, which would help implement prevention and control measures to prevent future risks of biting and LF transmission in Beijing.

Patterns and socioeconomic differences in secondhand exposure to cigarettes, e-cigarettes, and heated tobacco products at home in Hong Kong adolescents.

Smoke or aerosols from cigarettes, e-cigarettes (ECs), or heated tobacco products (HTPs) are harmful. Yet, there is little knowledge about the specific patterns of secondhand tobacco exposure by source within household settings and the socioeconomic status (SES) differences in adolescents. We used territory-representative student data from a cross-sectional school-based survey in 2020-2021 to calculate the weighted prevalence of secondhand exposure to cigarettes, e-cigarettes, and HTPs in the past seven days. Parental education and perceived family affluence were used as indicators of socioeconomic status. Generalized linear mixed models were used to analyze associations. Among 22039 participants, 29.8% reported any secondhand tobacco exposure (SH-Any) at home, primarily from cigarettes (27.4%), followed by e-cigarettes (4.0%) and HTPs (0.9%). Tertiary parental education level was associated with lower SH-Any exposure (Adjusted odds ratio, AOR=0.49; 95% CI: 0.45-0.53, p<0.001), fewer exposure days (β= -0.685, p<0.001), lower exposure to cigarettes (SH-CC) (AOR=0.49; 95% CI: 0.45-0.54, p<0.001) and to e-cigarettes or HTPs (SH-EC/HTP) (AOR=0.57; 95% CI: 0.45-0.71, p<0.001). 'Poor' family affluence was associated with higher exposures [AOR(SH-Any) =1.14; 95% CI: 1.06-1.22, p=0.001; β(days)=0.160, p<0.001; AOR(SH-CC) =1.15; 95% CI: 1.07-1.24, p<0.001], except for SH-EC/HTP exposure, which was higher in students in an affluent family (AOR =1.66; 95% CI: 1.25-2.21, p<0.001). Significant SES differences in SH-EC/HTP exposure were found only in groups with low parental education level. Dose-response relationships were found between lower SH-Any and SH-CC and higher SES categories (p for trend<0.001). Adolescents experienced a high prevalence of tobacco smoke exposure at home, primarily from cigarettes. Higher SES was associated with lower tobacco exposure, except for SH-EC/HTP, which was higher among adolescents from affluent families. Additionally, high parental education level was protective against exposure to SH-EC/HTP. Comprehensive control measures to reduce the use of these tobacco products are needed to protect adolescents of diverse socioeconomic backgrounds.

Evaluation of the impact of erosion control measures on dam siltation and upstream erosion using radioisotope technique 7Be and MUSLE model in the watershed upstream of Allal El Fassi dam, Morocco

Water erosion poses a significant threat to the sustainability of natural resources and hydro-agricultural infrastructure, particularly in the Mediterranean region, including Morocco. The Allal El Fassi watershed faced such challenges and underwent anti-erosion measures between 2008 and 2014. This study aims to evaluate the effectiveness of these measures in mitigating dam siltation within the watershed. The methodologies employed include the utilization of the MUSLE model, optimized with bathymetric surveys of the dam, to estimate the amount of sediment reaching the dam and derive the P-factor associated with the implemented anti-erosion measures. Additionally, the radioisotope technique was utilized to assess erosion rates at managed and unmanaged sites within the watershed. The results obtained using the MUSLE model and bathymetric data revealed a noteworthy reduction in mean annual soil loss within the timeframe of 2002–2010 to 2010–2013, resulting in a 13.9% decrease in sediment reaching the dam. Furthermore, variations in the P-factor of erosion control measures were observed, ranging from 0.31 to 0.52 during the respective periods. Utilizing the radionuclide 7Be, erosion rates ranging from 6.8 to 25.3 t.ha−1 were determined for the studied plots, facilitating the calculation of P-factors for specific erosion control measures. Significantly, gabion check dams displayed a P-factor of 0.47, dry stone barriers had a P-factor of 0.41, fruit trees with basins showed a P-factor of 0.51, and enclosures exhibited a P-factor of 0.67. These findings suggest a causal relationship between the implementation of erosion control measures and the reduction in sedimentation rates at the Allal El Fassi Dam, highlighting the interdependence between the two phenomena.

Sensitivity Analysis and Optimal Control of Cocoa Black Pod Disease Caused by Phytophora Margakarya

To address the critical threat black pod disease poses to global cocoa production and farmer income, this study developed a novel mathematical model that utilizes a system of ordinary differential equations to capture the interactions between various stages of cocoa pods (susceptible cherelles, young/mature pods, ripe pods) and their disease state (exposed, infected). Additionally, the model incorporates the dynamics of the disease-causing pathogen population. Employing Pontryagin’s Maximum Principle, the model optimizes control strategies that minimize disease impact. This optimization identifies the efficient allocation of resources, timing of interventions, and deployment of control measures like infected pod removal, fungicides, and sanitation practices. The finding of the study reveals that control measure u3 which is rouging (pod removal) and any one of the remaining control measures is best for the treatment of cocoa black pod disease caused by Phytophora Megarkaya. These findings translate into valuable, data-driven recommendations for cocoa farmers and disease management professionals. By strategically combining infected pod removal, targeted fungicide use, and environmental management practices, farmers can significantly reduce disease severity, enhance cocoa production, and promote a more sustainable cocoa industry.

Seroprevalence and levels of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies among medical students

Seroprevalence and levels of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies among medical students

Listeria monocytogenes from Food Products and Food Associated Environments: Antimicrobial Resistance, Genetic Clustering and Biofilm Insights

Listeria monocytogenes, a foodborne pathogen, exhibits high adaptability to adverse environmental conditions and is common in the food industry, especially in ready-to-eat foods. L. monocytogenes strains pose food safety challenges due to their ability to form biofilms, increased resistance to disinfectants, and long-term persistence in the environment. The aim of this study was to evaluate the presence and genetic diversity of L. monocytogenes in food and related environmental products collected from 2014 to 2022 and assess antibiotic susceptibility and biofilm formation abilities. L. monocytogenes was identified in 13 out of the 227 (6%) of samples, 7 from food products (meat preparation, cheeses, and raw milk) and 6 from food-processing environments (slaughterhouse-floor and catering establishments). All isolates exhibited high biofilm-forming capacity and antibiotic susceptibility testing showed resistance to several classes of antibiotics, especially trimethoprim-sulfamethoxazole and erythromycin. Genotyping and core-genome clustering identified eight sequence types and a cluster of three very closely related ST3 isolates (all from food), suggesting a common contamination source. Whole-genome sequencing (WGS) analysis revealed resistance genes conferring resistance to fosfomycin (fosX), lincosamides (lin), fluoroquinolones (norB), and tetracycline (tetM). In addition, the qacJ gene was also detected, conferring resistance to disinfecting agents and antiseptics. Virulence gene profiling revealed the presence of 92 associated genes associated with pathogenicity, adherence, and persistence. These findings underscore the presence of L. monocytogenes strains in food products and food-associated environments, demonstrating a high virulence of these strains associated with resistance genes to antibiotics, but also to disinfectants and antiseptics. Moreover, they emphasize the need for continuous surveillance, effective risk assessment, and rigorous control measures to minimize the public health risks associated to severe infections, particularly listeriosis outbreaks. A better understanding of the complex dynamics of pathogens in food products and their associated environments can help improve overall food safety and develop more effective strategies to prevent severe health consequences and economic losses.

Control of Sclerotinia sclerotiorum via an RNA interference (RNAi)-mediated targeting of SsPac1 and SsSmk1.

The study evaluates the potential of Spray-Induced Gene Silencing and Host-Induced Gene Silencing for sustainable crop protection against thebroad-spectrum necrotrophic fungus Sclerotinia sclerotiorum. Sclerotinia sclerotiorum (Lib.) de Bary, an aggressive ascomycete fungus causes white rot or cottony rot on a broad range of crops including Brassica juncea. The lack of sustainable control measures has necessitated biotechnological interventions such as RNA interference (RNAi) for effective pathogen control. Here we adopted two RNAi-based strategies-Spray-Induced Gene Silencing (SIGS) and Host-Induced Gene Silencing (HIGS) to control S. sclerotiorum. SIGS was successful in controlling white rot on Nicotiana benthamiana and B. juncea by targeting SsPac1, a pH-responsive transcription factor and SsSmk1, a MAP kinase involved in fungal development and pathogenesis. Topical application of dsRNA targeting SsPac1 and SsSmk1 delayed infection initiation and progression on B. juncea. Further, altered hyphal morphology and reduced radial growth were also observed following dsRNA application. We also explored the impact of stable dsRNA expression in A. thaliana against S. sclerotiorum. In this report, we highlight the utility of RNAi as a biofungicide and a tool for preliminary functional genomics.