Analysis of SARS-CoV-2 variants from 24,181 patients exemplifies the role of globalisation and zoonosis in pandemics

After the end of the first epidemic episode of SARS-CoV-2 infections, as cases began to rise again during the summer of 2020, we at IHU Mediterranee Infection in Marseille, France, intensified the genomic surveillance of SARS-CoV-2, and described the first viral variants. In this study, we compared the incidence curves of SARS-CoV-2-associated deaths in different countries and reported the classification of SARS-CoV-2 variants detected in our institute, as well as the kinetics and sources of the infections. We used mortality collected from a COVID-19 data repository for 221 countries. Viral variants were defined based on ≥5 hallmark mutations shared by ≥30 genomes. SARS-CoV-2 genotype was determined for 24,181 patients using next-generation genome and gene sequencing (in 47% and 11% of cases, respectively) or variant-specific qPCR (in 42% of cases). Sixteen variants were identified by analysing viral genomes from 9,788 SARS-CoV-2-diagnosed patients. Our data show that since the first SARS-CoV-2 epidemic episode in Marseille, importation through travel from abroad was documented for seven of the new variants. In addition, for the B.1.160 variant of Pangolin classification (a.k.a. Marseille-4), we suspect transmission from mink farms. In conclusion, we observed that the successive epidemic peaks of SARS-CoV-2 infections are not linked to rebounds of viral genotypes that are already present but to newly-introduced variants. We thus suggest that border control is the best mean of combating this type of introduction, and that intensive control of mink farms is also necessary to prevent the emergence of new variants generated in this animal reservoir.

Efektivitas Pengendalian Penyakit Tungro secara Terpadu dengan Pendekatan Pengendalian Biointensif

<p>Tungro disease is one of the obstacles to increase the national rice production program. In some areas, this important disease is endemic. On the one hand, some farmers in controlling plant pests and diseases still use pesticides, which negatively impact health and the environment. On the other hand, environmentally friendly tungro disease control technology is available. This study aims to determine an environmentally friendly integrated control technique for tungro disease consisting of resistant varieties, biopesticides, and conservation of natural enemies with flowering plants in suppressing green leafhopper populations and the incidence of tungro transmission in infection-sensitive plant stage. The test area is located in Lanrang,Sidrap at the Experimental field of Tungro Disease Research Station, Lanrang Sidrap, South Sulawesi, Indonesia from April to September 2017, using a split-plot design. Main plots are: 1) Biointensive control plots, using flowering plants (refugia) and pest control with andrometa which is a mixture of the entomopathogenic fungus Metharizium anisopliae and sambiloto extract; 2) Conventional plots, without flowering plants and pest control using pesticides. As sub-plots are rice varieties: 1) TN1, 2) IR64, and 3) Inpari-9 Elo which differ in resistance to tungro. Observations were made at 2, 4, 6, and 8 weeks after planting (MST). The results showed that the population of green leafhoppers in the TN1, both in the bio-intensive control plot and in the conventional control plot, was higher than the other two varieties. The population of natural enemies in bio-intensive control consists of 10 predator families and the conventional control consists of 9 predator families. The effectiveness of bio-intensive control has an effect on decreasing the population of green leafhoppers and the diversity of natural enemies, and has no significant effect on the incidence of tungro transmission, and has no effect on grain yield. Therefore, biointensive control needs to be developed to create a pesticide-free agricultural environment.</p>

Predicting future ocular Chlamydia trachomatis infection prevalence using serological, clinical, molecular, and geospatial data

Trachoma is an infectious disease characterized by repeated exposures to Chlamydia trachomatis (Ct) that may ultimately lead to blindness. Certain areas, particularly in Africa, pose persistent challenges to elimination of trachoma as a public health problem. Efficiently identifying communities with high infection burden could help target more intensive control efforts. We hypothesized that IgG seroprevalence in combination with geospatial layers, machine learning, and model-based geostatistics would be able to accurately predict future community-level ocular Ct infections detected by PCR. We used measurements from 40 communities in the hyperendemic Amhara region of Ethiopia. Median Ct infection prevalence among children 0-5 years old increased from 6% at enrollment to 29% by month 36. At baseline, correlation between seroprevalence and Ct infection was stronger among children 0-5 years old (ρ = 0.77) than children 6-9 years old (ρ = 0.48), and stronger than the correlation between clinical trachoma and Ct infection (0-5y ρ = 0.56; 6-9y ρ = 0.40). Seroprevalence was the strongest concurrent predictor of infection prevalence at month 36 among children 0-5 years old (cross-validated R2 = 0.75, 95% CI: 0.58-0.85), though predictive performance declined substantially with increasing temporal lag between predictor and outcome measurements. Geospatial variables, a spatial Gaussian process, and stacked ensemble machine learning did not meaningfully improve predictions. Serological markers among children 0-5 years old may be an objective, programmatic tool for identifying communities with high levels of active ocular Ct infections, but accurate, future prediction in the context of changing transmission remains an open challenge.

Understanding Farmer and Government Measure in Rat Pests Control in Rice Fields

This paper discusses the control of rat pets through highlighting its population growth, ecosystem, types and possible mechanism to use. During extended periods of fallow, rice field rats tend to congregate in escape places (refuge regions) such as bushes, yards, or rice warehouses. Rice plants suffered damage equivalent to five times their feeding requirements when rats were present. Rats damage plants from the tiller stage to the maximal tiller stages by devouring the growth point and the soft base of the stem while leaving the other portions of the plant unharmed. Without intensive control efforts (since the start of MT1), the rat population density on MT2 is confirmed to be higher and poses a serious threat to the success of MT2 harvesting. In one rice growing season, there is one population peak so in the rice-paddy-fallow cropping pattern there are two (2) population peaks.

Resistance Monitoring of Nilaparvata lugens Stall against Pymetrozine Insecticide with Determination of Diagnostic Concentrations

Nilaparvata lugens Stall is one of the main insect pests on rice crops. Intensive control of this pests using insecticides has resulted in the development of insect resistance. This study aimed to find out the level of resistance of the N. lugens population to pymetrozine insecticides by determining the diagnostic concertations. N. lugens was collected from five endemic areas in Central Java Province from October 2019 to June 2020. The data from the bioassay test were analyzed with probit analysis to obtain the LC50 value. The results of the sensitivity test showed that the Kajen population has the highest RF value (2.47), while the Karanganyar population which has the lowest RF value (1) was the most sensitive population. The determined diagnostic concentration was LC95 = 25.52 ppm with the lowest concentration limit of 7.67 ppm and the highest of 30.05 ppm. To conclude, the determined diagnostic concentration (LC95 = 25.52 ppm) is effective for detecting the susceptibililty of N. lugens population. This finding would be beneficial for monitoring resistance of N. lugens population against pymetrozine insecticides in the field.

Modelling of malaria risk, rates, and trends: A spatiotemporal approach for identifying and targeting sub-national areas of high and low burden

While mortality from malaria continues to decline globally, incidence rates in many countries are rising. Within countries, spatial and temporal patterns of malaria vary across communities due to many different physical and social environmental factors. To identify those areas most suitable for malaria elimination or targeted control interventions, we used Bayesian models to estimate the spatiotemporal variation of malaria risk, rates, and trends to determine areas of high or low malaria burden compared to their geographical neighbours. We present a methodology using Bayesian hierarchical models with a Markov Chain Monte Carlo (MCMC) based inference to fit a generalised linear mixed model with a conditional autoregressive structure. We modelled clusters of similar spatiotemporal trends in malaria risk, using trend functions with constrained shapes and visualised high and low burden districts using a multi-criterion index derived by combining spatiotemporal risk, rates and trends of districts in Zambia. Our results indicate that over 3 million people in Zambia live in high-burden districts with either high mortality burden or high incidence burden coupled with an increasing trend over 16 years (2000 to 2015) for all age, under-five and over-five cohorts. Approximately 1.6 million people live in high-incidence burden areas alone. Using our method, we have developed a platform that can enable malaria programs in countries like Zambia to target those high-burden areas with intensive control measures while at the same time pursue malaria elimination efforts in all other areas. Our method enhances conventional approaches and measures to identify those districts which had higher rates and increasing trends and risk. This study provides a method and a means that can help policy makers evaluate intervention impact over time and adopt appropriate geographically targeted strategies that address the issues of both high-burden areas, through intensive control approaches, and low-burden areas, via specific elimination programs.

Organization Of Teaching Mathematics Of Scholar Students In The Conditions Of A Credit - Modular Training System

This paper examines the methodology for organizing training in the course of Higher Mathematics in the conditions of a credit - modular training system, the role of intensive control of students 'knowledge, which increases the activity of students in studying the discipline, preparing them for classes and completing tasks in a timely manner, as well as students' independent work. It is possible to improve teaching mathematics through the use of elements of individual, differentiated, problem-solving and programmed teaching. Moreover, a special role is given to the intensive control of students' knowledge, which increases the activity of students in the study of this discipline, their preparation for classes and their timely completion of tasks, as well as their independent work.

Induced Expression of kir6.2 in A1 Astrocytes Propagates Inflammatory Neurodegeneration via Drp1-dependent Mitochondrial Fission

Glia-mediated inflammatory processes are crucial in the pathogenesis of Parkinson’s disease (PD). As the most abundant cells of the brain and active participants in neuroinflammatory responses, astrocytes largely propagate inflammatory signals and amplify neuronal loss. Hence, intensive control of astrocytic activation is necessary to prevent neurodegeneration. In this study, we report that the astrocytic kir6.2, as a abnormal response after inflammatory stimuli, promotes the reactivity of A1 neurotoxic astrocytes. Using kir6.2 knockout (KO) mice, we find reversal effects of kir6.2 deficiency on A1-like astrocyte activation and death of dopaminergic neurons in lipopolysaccharide (LPS)-induced mouse models for PD. Further in vitro experiments show that aberrant kir6.2 expression induced by inflammatory irritants in astrocytes mediates the dynamin-related protein 1 (Drp1)-dependent excessive mitochondrial fragmentation and results in mitochondrial malfunctions. By deleting kir6.2, astrocytic activation is reduced and astrocytes-derived neuronal injury is prevented. We therefore conclude that astrocytic kir6.2 can potentially elucidate the pathology of PD and promote the development of therapeutic strategies for PD.

Bio-intensive integrated control of tungro disease in the rice field

This research aims to gain the technology of bio-intensive integrated control of tungro. The experiments were done in a split-plot design with three replications. The main plot consisted of Bio-intensive integrated control, compared to Conventional control. The subplots are: 1) the susceptible varieties (TN1), 2) green leafhopper–resistant varieties (IR64), and 3) tungro resistant varieties (Inpari 9 Elo). The subplots are 10 m x 10 m, and every subplot is replicated three times. Variables observed were the population density of green leafhopper (GLH) and the predators, the percentage of tungro incidence, and the grain yield. The results showed that the population of GLH in the plots of bio-intensive integrated control (27.32, 2.34, 4.83, and 5.16) was lower than the population of GLH in conventional control (34.00, 21.17, 7.84, and 6.50). The GLH population density tends to be higher in varieties TN1 than the other varieties both in bio-intensive and conventional control. It is found that 12 species of predator exist in all varieties of bio-intensive control and conventional plots. At 8 WAT the infection of RTV on all varieties in bio-intensive plot control is lower (0.67 - 2.67%) than the incidence of tungro in conventional plot control (3.00 - 8.67%).

Quantifying the dynamics of COVID-19 burden and impact of interventions in Java, Indonesia

Measuring COVID-19 spread remains challenging in many countries due to testing limitations. In Java, reported cases and deaths increased throughout 2020 despite intensive control measures, particularly within Jakarta and during Ramadan. However, underlying trends are likely obscured by variations in case ascertainment. COVID-19 protocol funerals in Jakarta provide alternative data indicating a substantially higher burden than observed within confirmed deaths. Transmission estimates using this metric follow mobility trends, suggesting earlier and more sustained intervention impact than observed in routine data. Modelling suggests interventions have lessened spread to rural, older communities with weaker healthcare systems, though predict healthcare capacity will soon be exceeded in much of Java without further control. Our results highlight the important role syndrome-based measures of mortality can play in understanding COVID-19 transmission and burden.