Microbiological Antibiotic Assay Validation of Gentamicin Sulfate Using Two-Dose Parallel Line Model (PLM)

Nowadays, microbiological assay is still widely used with several antibiotics that are composed of a mixture of related active compounds. However, obtaining a reasonably valid determination of the potency is dependent on the validity and suitability of the assay design. The present work aimed to validate an assay design for an aminoglycoside antibiotic (Gentamicin Sulfate) using a two-dose Parallel Line Model agar diffusion assay in a large 8×8 rectangular plate. All preparatory procedures were done following the United States Pharmacopeia and the inhibition zones were measured using a digital caliper to the nearest 0.01 mm. Analysis of variance in compendial requirements for regression and parallelism were found to satisfactorily meet the acceptance criteria. Specificity was achieved for the product under investigation with no detectable IZ that could be found for all components except the antibiotic. The validation method showed an acceptable linearity of r2≥0.98. Accuracy and precision parameters showed RSD (%)<2. All relative error value estimates were below 4%. The proposed validation design for 32×32 cm antibiotic plates yielded valid results and can be projected for the routine Quality Control analysis of the antibiotic material, especially that which is incorporated into a finished medicinal dosage form. Doi: 10.28991/HIJ-2021-02-04-04 Full Text: PD

Dendrogram Analysis and Statistical Examination for Total Microbiological Mesophilic Aerobic Count of Municipal Water Distribution Network System

The microbiological quality of water for human consumption is a critical safety aspect that should not be overlooked, especially when considering facilities for healthcare and the treatment of ill populations. Thus, the biological stability of water is crucial for the distribution network that delivers potable water to the final users for consumption and other human activities. The present work aimed to study a municipal distribution network system for city water within a healthcare facility. The implementation of the statistical analysis was conducted over long-term data collection, and the comparative study for the microbiological count of the water samples - from different points-of-use was assessed using the non-parametric analysis of the Kruskal-Wallis test. The comparative study involved a preliminary general one-way Analysis of Variance (ANOVA) followed by ad-hoc pairwise comparison. The statistical study involved a correlation matrix and a dendrogram to elucidate the level of association between different sections in the network. The ports C4 and C13 were at the trough in the microbiological count, in contrast to C13, which showed the highest level of the average microbial density. Despite a low to moderate level of correlation between the datasets of the water network, the tree diagram (dendrogram) analysis showed remarkable clustering. Use points could be grouped into three dense groups based on abrupt cuts in the similarity value. The study was useful in the analysis of the pattern and behavior of the microbial quality in a distribution water network in a specific area of the study. This work in turn would help in investigating the areas of improvement and defect spotting, in addition to assessing the biological stability of the water distribution system. The study could be extended to cover other different processed water networks, such as distilled, deionized, and purified water, as well as Water-For-Injection (WFI). Doi: 10.28991/HIJ-2022-03-01-03 Full Text: PD

Correlation between COVID-19 morbidity and mortality rates in Japan and local population density, temperature and absolute humidity

This study analyzed the morbidity and mortality rates of the COVID-19 pandemic in different prefectures of Japan. Under the constraint that daily maximum confirmed deaths and daily maximum cases should exceed 4 and 10, respectively, 14 prefectures were included, and cofactors affecting the morbidity and mortality rates were evaluated. In particular, the number of confirmed deaths was assessed excluding the cases of nosocomial infections and nursing home patients. A mild correlation was observed between morbidity rate and population density (R2=0.394). In addition, the percentage of the elderly per population was also found to be non-negligible. Among weather parameters, the maximum temperature and absolute humidity averaged over the duration were found to be in modest correlation with the morbidity and mortality rates, excluding the cases of nosocomial infections. The lower morbidity and mortality are observed for higher temperature and absolute humidity. Multivariate analysis considering these factors showed that determination coefficients for the spread, decay, and combined stages were 0.708, 0.785, and 0.615, respectively. These findings could be useful for intervention planning during future pandemics, including a potential second COVID-19 outbreak.Comment: International Journal of Environmental Research and Public Health, 202

Influence of Absolute Humidity, Temperature and Population Density on COVID-19 Spread and Decay Durations: Multi-prefecture Study in Japan

This study analyzed the spread and decay durations of the COVID-19 pandemic in different prefectures of Japan. During the pandemic, affordable healthcare was widely available in Japan and the medical system did not suffer a collapse, making accurate comparisons between prefectures possible. For the 16 prefectures included in this study that had daily maximum confirmed cases exceeding ten, the number of daily confirmed cases follow bell-shape or log-normal distribution in most prefectures. A good correlation was observed between the spread and decay durations. However, some exceptions were observed in areas where travelers returned from foreign countries, which were defined as the origins of infection clusters. Excluding these prefectures, the population density was shown to be a major factor affecting the spread and decay patterns, with R2=0.39 (p<0.05) and 0.42 (p<0.05), respectively, approximately corresponding to social distancing. The maximum absolute humidity was found to affect the decay duration normalized by the population density (R2>0.36, p <0.05). Our findings indicate that the estimated pandemic spread duration, based on the multivariate analysis of maximum absolute humidity, ambient temperature, and population density (adjusted R2=0.53, p-value<0.05), could prove useful for intervention planning during potential future pandemics, including a second COVID-19 outbreak.Comment: Submitted to: International Journal of Environmental Research and Public Healt