Spatiotemporal modeling of schistosomiasis in Ghana: linking remote sensing data to infectious disease

More than 90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. The use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. The transmission of schistosomiasis, a disease acquired from contact with contaminated surface water, requires specific environmental conditions to sustain freshwater snails. If a connection between schistosomiasis and remotely sensed environmental variables can be established, then cost effective and current disease risk predictions can be made available. Schistosomiasis transmission has unknown seasonality, and the disease is difficult to study due to a long lag between infection and clinical symptoms. To overcome these challenges, we employed a comprehensive 15-year time-series built from remote sensing feeds, which is the longest environmental dataset to be used in the application of remote sensing to schistosomiasis. The following environmental variables will be used in the model: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique. This technique, improves upon the conventional Köppen-Geiger method, which has been the primary climate classification system in use the past 100 years. These predictor variables will be regressed against 8 years of national health data in Ghana, the largest health dataset of its kind to be used in this context, and acquired from freely available satellite imagery data. A benefit of remote sensing processing is that it only requires training and time in terms of resources. The results of a fixed effects model can be used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.Published versio

Investigating seasonal patterns in enteric infections: a systematic review of time series methods

Foodborne and waterborne gastrointestinal infections and their associated outbreaks are preventable, yet still result in significant morbidity, mortality, and revenue loss. Many enteric infections demonstrate seasonality, or annual systematic periodic fluctuations in incidence, associated with climatic and environmental factors. Public health professionals use statistical methods and time series models to describe, compare, explain, and predict seasonal patterns. However, descriptions and estimates of seasonal features, such as peak timing, depend on how researchers define seasonality for research purposes and how they apply time series methods. In this review, we outline the advantages and limitations of common methods for estimating seasonal peak timing. We provide recommendations improving reporting requirements for disease surveillance systems. Greater attention to how seasonality is defined, modeled, interpreted, and reported is necessary to promote reproducible research and strengthen proactive and targeted public health policies, intervention strategies, and preparedness plans to dampen the intensity and impacts of seasonal illnesses. © 2022 Cambridge University Press. All rights reserved

Biological treatment of sewage from petroleum-chemical production

Sewage waters from styrene and propellent oxide production are studied for the possibility of their local aerobic treatment using immobilized microorganisms. Modelling of sewage treatment in the plant consisting of four successively connected biotanks with immobilized microflora has proved the ability of 95-97% treatment from organic pollutants whose initial concentration corresponds to COD 5.2 g/l. Gram-negative bacteria and, in the first place, strain SP1, whose portion in the successively functioning biotanks increased from 21 to 95%, are of great significance in treatment of real industrial sewage of the above production

Application of Membrane Filtration to Prevent Microbial Contamination of Lysimeter Water

Ultrafiltration is suggested for the elimination of artifacts evolved from the biochemical transformation of water-soluble organic substances in lysimeter collectors. A membrane filter installed between the vessel of the lysimeter and its collector provides the separation of microbial cells from water-soluble organic substances immediately at the infiltrate accumulation

Modeling of lactic acid fermentation of leguminous plant juices

Lactic acid fermentation of leguminous plant juices was modeled to provide a comparative efficiency assessment of the previously selected strains of lactic acid bacteria as potential components of starter cultures. Juices of the legumes fodder galega, red clover, and alfalfa were subjected to lactic acid fermentation in 27 variants of the experiment. Local strains (Lactobacillus sp. RS 2, Lactobacillus sp. RS 3, and Lactobacillus sp. RS 4) and the collection strain Lactobacillus plantarum BS 933 appeared the most efficient (with reference to the rate and degree of acidogenesis, ratio of lactic and acetic acids, and dynamics of microflora) in fermenting fodder galega juice; Lactobacillus sp. RS 1, Lactobacillus sp. RS 2, Lactobacillus sp. RS 3, Lactobacillus sp. RS 4, and L. plantarum BS 933 were the most efficient for red clover juice. Correction of alfalfa juice fermentation using the tested lactic acid bacterial strains appeared inefficient, which is explainable by its increased protein content and a low level of acids produced during fermentation. © MAIK "Nauka/Interperiodica", 2006

Aerobic degradation of 2,4,6-trinitrotoluene by the yeast strain Geotrichum candidum AN-Z4

The yeast strain Geotrichum candidum AN-Z4 isolated from an anthropogenically polluted site was able to transform 2,4,6-trinitrotoluene (TNT) via the formation of unstable intermediate hydride Meisenheimer complexes with their subsequent destruction and accumulation of nitrite and nitrate ions as the end mineral forms of nitrogen. Aeration of the medium promoted more profound destruction of this xenobiotic by the strain G. candidum AN-Z4 than static conditions. The yeast strain was shown to produce citrate, succinate, and isocitrate, which sharply acidified the medium and influenced the TNT destruction. Two possible pathways of TNT biodegradation were confirmed experimentally: (1) via the destruction of the TNT-monohydride complex (3-H--TNT) and (2) via the destruction of one protonated TNT-dihydride complex (3,5-2H--TNT · H+). The strain G. candidum AN-Z4, due to its ability for TNT degradation, may be promising for bioremediation of TNT-contaminated soil and water. © Pleiades Publishing, Ltd., 2010

Influence of pH on 2,4,6-trinitrotoluene degradation by Yarrowia lipolytica

The microbial reduction of the aromatic ring of 2,4,6-trinitrotoluene (TNT) can lead to its complete destruction. The acid-tolerant yeast Yarrowia lipolytica AN-L15 transformed TNT through hydride ion-mediated reduction of the aromatic ring (as the main pathway), resulting in the accumulation of nitrite and nitrate ions, as well as through nitro group reduction (as minor pathway), resulting in hydroxylamino- and aminoaromatics. TNT transformation depended on the yeasts' ability to acidify the culture medium through the production of organic acids. Aeration and a low medium buffer capacity favored yeast growth and resulted in rapid acidification of the medium, which influenced the rate and extent of TNT transformation. This is the first time that nitrate has been detected as a major product of microbial TNT degradation, and this work demonstrates the importance of pH on TNT biotransformation. The ability of Y. lipolytica AN-L15 to reduce the TNT aromatic ring to form TNT-hydride complexes, followed by their denitration, makes this strain a potential candidate for bioremediation of sites contaminated with explosives. © 2010 Elsevier Ltd. All rights reserved