Radiation sensitivity of water- borne multi drug resistant Escherichia coli

The spread of antibiotic-resistant microorganisms in the environment is recognized widely as an important public health issue, with concerns about future ability to treat infectious diseases. The main risk to public health is that the resistance genes are transferred from environmental bacteria to human pathogens. Safe water is one of the most important needs in public health in the twenty first century. Radiation sensitivity (D10) is defined as the radiation dose (kGy) required to reduce the number of that  microorganism by 10-fold. The aim of this paper is to determine the association between multiple antibiotic resistance and radiation sensitivity (D10).Four hundred and sixty four (464) water samples were collected for assessment. E. coli isolation and identification were done using API 20E, and a PCR based DNA STRIP technology that allows simultaneous detection of virulence genes and confirmation of E. coli isolates. Antibiotic  susceptibility testing was also conducted using the Kirby-bauer method. Radiation sensitivity was done using a cobalt 60 source. Sixty-three percent (63%) of the multidrug resistant E. coli strains recorded a multiple antibiotic resistance (MAR) index value of >0.2. The mean radiation sensitivity (D10) of the E. coli isolates is 0.33±0.11 kGy. The study confirmed a high prevalence of multiple antibiotic resistances in E. coli isolates. Lastly, there is no association between multiple antibiotic resistant indexes and radiation sensitivity (D10) of antibiotic resistant E. coli.Keywords: Antibiotics, Escherichia coli, water-borne, multi drug resistant  radiation, Sensitivity

Cross-seasonal analysis of bacteriological profile of water sources as a disease risk measure

Water is a natural resource and is essential to sustain life. Poor drinking water quality is the cause of several diseases. The aim of this paper was to investigate bacteriological profile of water sources as a measure of disease risk, aimed at providing useful information towards rural water resources management. Five hundred and twenty bacterial isolates (520) were obtained from waters samples collected during the period of study. Majority of the Isolates (305) representing 58.65% of the total were obtained during the dry season, as against (205) representing 41.35% in the rainy season. There was a statistical differences (P> 0.05) of the microbes isolated seasonally. The highest occurring was Klebsiella spp. (9.83±6.99, P> 0.05) in the dry season and the least Shigella spp. P> 0.05. Furthermore dam water sources was observed to poses a high disease risk among the five water sources investigated, whiles borehole water sources possess a lower diseases risk. An alarming observation was the presences of bacteria of public health importance in the water sources. These included Shigella spp. (dysentery), Salmonella typhi (typhoid fever and acute diarrhoeal infection), Salmonella typhi (typhoid fever), and Vibrio cholerea (cholera). In a nutshell, to reduce the level of bacterial contamination of drinking water sources there should be an incessant education on issues such as: environmental awareness, (cultivation sanitation habits and ensure that their surroundings and water sources are not indiscriminately polluted), causes, modes of transmission and prevention of water and sanitation related diseases.Keywords: E. coli, water, Public health and diseas

Mycobacterial species causing pulmonary tuberculosis At the korle bu teaching hospital, Accra,

Objective: Characterize mycobacterial species causing pulmonary tuberculosis (PTB) at the Korle-Bu Teaching Hospital in Ghana.Design: Sputum smear positive samples, two (2) from 70 patients diagnosed as having tuberculosis, after they had consented, were collected from the Korle-Bu Teaching Hospital Chest Clinic betweenJanuary and July 2003. Setting: Korle-Bu Teaching Hospital Chest Clinic, Accra. Results: Sixty-four mycobacterial isolates wereobtained and confirmed as members of Mycobacterium tuberculosis complex by colonial morphology and conventional biochemical assays. Fortyseven (73%) were M. tuberculosis, the human strain, 2 (3%) M. bovis, the bovine strain, 13 (20%) M. africanum I (West Africa type), and 2 (3%) M. africanum II (East Africa type). Conclusion: The results indicate that, there are various strains causing PTB at the Korle-BuTeaching Hospital and of great concern is M. bovis, which mostly causes extra-PTB in humans but found to cause PTB in this study. This calls for the need to conduct a nationwide survey using bothconventional and molecular techniques to characterize various mycobacterial species causing TB in Ghana. This will result in better understanding of the various strains circulating in the country andinform individual TB treatment regimen especially the inclusion or exclusion of pyrazinamide

The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. METHODS: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. FINDINGS: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). INTERPRETATION: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. Funding: Bill & Melinda Gates Foundation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings: The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation: Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. Funding: Bill & Melinda Gates Foundation

National population-based tuberculosis prevalence survey in Ghana, 2013

BACKGROUND: The prevalence of tuberculosis (TB) disease is one of the three main indicators used to assess the epidemiological burden of TB and the impact change of TB control; the other two are incidence and mortality. OBJECTIVE : To estimate the prevalence of TB disease among adults in Ghana. METHODS : A nationally representative cross-sectional survey was conducted. Participants were screened for TB using interview and chest X-ray (CXR). For those participants with cough-2 weeks and/or abnormal CXR, spot andmorning sputumspecimens were collected and examined by smear microscopy and culture. RESULT S : The study revealed that the prevalence of smear-positive TB among adults (age-15 years) was 111 (95%CI 76-145) and that of bacteriologically confirmed TB was 356 (95%CI 288-425) per 100 000 population. Males and older people had a higher prevalence than their counterparts. The majority of TB cases were smear-negative and had an abnormal CXR without reported chronic cough. CONCLUS ION: The survey revealed much higher TB disease burden than previously estimated. This implies that the programme needs more effort and resources to find undiagnosed and unreported cases. The higher proportion of smear-negative and asymptomatic TB cases suggests the need to revise the existing screening and diagnostic algorithms

Socio-Behavioral Risk Factors Associated with Cryptosporidiosis in HIV/AIDS Patients Visiting the HIV Referral Clinic at Cape Coast Teaching Hospital, Ghana

bjective: To identify the socio-behavioral risk factors associated with cryptosporidiosis among HIV/AIDS patients with chronic diarrhea symptoms visiting the HIV referral clinic at Cape Coast Teaching Hospital, Ghana. Methods: A cross-sectional study was conducted among 50 HIV/AIDS patients with recurrent diarrhea. Questionnaires were administered to collect social and behavioral risk factors associated with Cryptosporidium and other opportunistic protozoan parasitic infections in HIV patients. Stool samples were collected for the diagnosis of enteric protozoan pathogens using modified Ziehl-Neelsen and acid-fast staining methods. CD4+ cells counts of study subjects were obtained from patients clinical records. The data obtained were analyzed using Pearson chi-square and multivariate-adjusted statistics tool on SPSS 16 for Windows. Results: Twenty-seven (54%) of the subjects were infected with enteric protozoan pathogens. The prevalences of Cryptosporidium, Cyclospora and Microsporidium infections were 46%, 32% and 16%, respectively. Cryptosporidium infection was significantly associated with drinking water (×2=13.528, p500 cells/mm3. Multivariate analysis showed that the risk factor for Cryptosporidium infection among HIV/AIDS patients was the source of drinking water (pipe borne water 76.2% prevalence: sachet water 25%; OR=0.10, 95%CI: 0.03-0.39, p<0.001). Conclusion: We report the risk factor for exposure of Cryptosporidium infection among HIV/AIDS patients for the first time in Ghana. The contamination of drinking water by protozoan parasites should be a public health concern. These results provide the stepping block to understand the transmission dynamics of Cryptosporidium and other opportunistic pathogens in HIV/AIDS infected patients in Ghana

National tuberculosis prevalence surveys in Africa, 2008\u20132016: an overview of results and lessons learned

Objective and methods: Worldwide, tuberculosis (TB) is the leading cause of death from a single infectious agent. In many countries, national TB prevalence surveys are the only way to reliably measure the burden of TB disease and can also provide other evidence to inform national efforts to improve TB detection and treatment. Our objective was to synthesise the results and lessons learned from national surveys completed in Africa between 2008 and 2016, to complement a previous review for Asia. Results: Twelve surveys completed in Africa were identified: Ethiopia (2010\u20132011), Gambia (2011\u20132013), Ghana (2013), Kenya (2015\u20132016), Malawi (2013\u20132014), Nigeria (2012), Rwanda (2012), Sudan (2013\u20132014), Tanzania (2011\u20132012), Uganda (2014\u20132015), Zambia (2013\u20132014) and Zimbabwe (2014). The eligible population in all surveys was people aged 6515&nbsp;years who met residency criteria. In total 588&nbsp;105 individuals participated, equivalent to 82% (range 57\u201396%) of those eligible. The prevalence of bacteriologically confirmed pulmonary TB disease in those 6515&nbsp;years varied from 119 (95% CI 79\u2013160) per 100&nbsp;000 population in Rwanda and 638 (95% CI 502\u2013774) per 100&nbsp;000 population in Zambia. The male:female ratio was 2.0 overall, ranging from 1.2 (Ethiopia) to 4.1 (Uganda). Prevalence per 100&nbsp;000 population generally increased with age, but the absolute number of cases was usually highest among those aged 35\u201344&nbsp;years. Of identified TB cases, 44% (95% CI 40\u201349) did not report TB symptoms during screening and were only identified as eligible for diagnostic testing due to an abnormal chest X-ray. The overall ratio of prevalence to case notifications was 2.5 (95% CI 1.8\u20133.2) and was consistently higher for men than women. Many participants who did report TB symptoms had not sought care; those that had were more likely to seek care in a public health facility. HIV prevalence was systematically lower among prevalent cases than officially notified TB patients with an overall ratio of 0.5 (95% CI 0.3\u20130.7). The two main study limitations were that none of the surveys included people &lt;15&nbsp;years, and 5 of 12 surveys did not have data on HIV status. Conclusions: National TB prevalence surveys implemented in Africa between 2010 and 2016 have contributed substantial new evidence about the burden of TB disease, its distribution by age and sex, and gaps in TB detection and treatment. Policies and practices to improve access to health services and reduce under-reporting of detected TB cases are needed, especially among men. All surveys provide a valuable baseline for future assessment of trends in TB disease burden