Optimizing health service location in a highly urbanized city: Multi criteria decision making and P-Median problem models for public hospitals in Jeddah City, KSA.

Rapid urbanization and population growth have increased the need for optimizing the location of health services in highly urbanized countries like Kingdom of Saudi Arabia (KSA). This study employs a multiple-criteria decision making (MCDM) approach, e.g., fuzzy overlay technique by combining the P-Median location-allocation model, for optimizing health services. First, a geodatabase, containing public hospitals, road networks and population districts, was prepared. Next, we investigated the location and services of five public hospitals in Jeddah city of KSA, by using a MCDM model that included a fuzzy overlay technique with a location-allocation model. The results showed that the allocated five hospitals served 94 out of 110 districts in the study area. Our results suggested additional hospitals must be added to ensure that the entire city is covered with timely hospital services. To improve the existing situation, we prioritized demand locations using the maximize coverage (MC) location problem model. We then used the P-Median function to find the optimal locations of hospitals, and then combined these two methods to create the MC-P-Median optimizer. This optimizer eliminated any unallocated or redundant information. Health planners can use this model to determine the best locations for public hospitals in Jeddah city and similar settings.

Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah.

Type-2 diabetes is a growing lifestyle disease mainly due to increasing physical inactivity but also associated with various other variables. In Saudi Arabia, around 58.5% of the population is deemed to be physically inactive. Against this background, this study attempts explore the spatial heterogeneity of Type-2 diabetes prevalence in Jeddah and to estimate various socio-economic and built environment variables contributing to the prevalence of this disease based on modelling by ordinary least squares (OLS), weighted regression (GWR) and multi-scale geographically weighted (MGWR). Our OLS results suggest that income, population density, commercial land use and Saudi population characteristics are statistically significant for Type-2 diabetes prevalence. However, by the GWR model, income, commercial land use and Saudi population characteristics were significantly positive while population density was significantly negative in this model for 70.6%, 9.1%, 26.6% and 58.7%, respectively, out of 109 districts investigated; by the MGWR model, the corresponding results were 100%, 22%, 100% and 100% of the districts. With the given data, the corrected Akaike information criterion (AICc), the adjusted R2, the log-likelihood and the residual sum of squares (RSS) indices demonstrated that the MGWR model outperformed the GWR and OLS models explaining 29% more variance than the OLS model, and 10.2% more than the GWR model. These results support the development of evidence-based policies for the spatial allocation of health associated resources for the control of Type-2 diabetes in Jeddah and other cities in the Arabian Gulf.

Impact and variability of social determinants of health on the transmission and outcomes of COVID-19 across the world: a systematic review protocol.

INTRODUCTION: The COVID-19 pandemic has exacerbated health inequalities across the globe, disproportionately affecting those with poor social determinants of health (SDOHs). It is imperative to understand how SDOH influences the transmission and outcomes (positive case, hospitalisation and mortality) of COVID-19. This systematic review will investigate the impact of a wide range of SDOHs across the globe on the transmission and outcomes of COVID-19. METHODS AND ANALYSIS: This review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol guidelines. We will search three electronic bibliographical databases (MEDLINE via PubMed, Embase and Scopus), as well as the WHO COVID-19 Global Research on Coronavirus Disease database. We will consider observational studies that report statistical relationships between the SDOHs (as listed in PROGRESS-Plus and Healthy People 2020) and COVID-19 transmission and outcomes. There will be no limitation on the geographical location of publications. The quality of included observational studies will be assessed using a modified version of the Newcastle-Ottawa Scale. A narrative synthesis without meta-analysis reporting standards will be used to report the review findings. ETHICS AND DISSEMINATION: This review will be based on published studies obtained from publicly available sources, and therefore, ethical approval is not required. We will publish the results of this review in a peer-reviewed journal, as well as present the study findings at a national conference. PROSPERO REGISTRATION NUMBER: CRD42021228818.

Using the location-allocation P-median model for optimising locations for health care centres in the city of Jeddah City, Saudi Arabia.

Considering spatial accessibility of health services is a critical part in the planning and management of health services. There is evidence that poor geographical locations can obstruct prompt basic health care services to some population sections. We developed a location-allocation P-median model for health centres after analysing their sites, demand location of health services and the road network in Jeddah, Saudi Arabia. This model attempts to optimize health care services network and to put forward location recommendations to maximise service coverage. Our model is shown to be useful as it provides a robust evidence base to urban planners and policymakers responsible for making spatial decisions for the development of the health sector. Besides, it follows the paradigm of new urbanism that encourages decentralisation of essential facilities including basic healthcare in cities, where emphasis is on offering all basic services within walkable distances of 15 min. or less.

Parasitic Disease Surveillance, Mississippi, USA.

Surveillance for soil-transmitted helminths, strongyloidiasis, cryptosporidiosis, and giardiasis was conducted in Mississippi, USA. PCR performed on 224 fecal samples for all soil-transmitted helminths and on 370 samples for only Necator americanus and Strongyloides stercoralis identified 1 S. stercoralis infection. Seroprevalences were 8.8% for Toxocara, 27.4% for Cryptosporidium, 5.7% for Giardia, and 0.2% for Strongyloides parasites.

Therapeutic Intervention of COVID-19 by Natural Products: A Population-Specific Survey Directed Approach.

To date very few promising leads from natural products (NP) secondary metabolites with antiviral and immunomodulatory properties have been identified for promising/potential intervention for COVID-19. Using in-silico docking studies and genome based various molecular targets, and their in vitro anti-SARS CoV-2 activities against whole cell and/or selected protein targets, we select a few compounds of interest, which can be used as potential leads to counteract effects of uncontrolled innate immune responses, in particular those related to the cytokine storm. A critical factor for prevention and treatment of SARS-CoV-2 infection relates to factors independent of viral infection or host response. They include population-related variables such as concurrent comorbidities and genetic factors critically relevant to COVID-19 health disparities. We discuss population risk factors related to SARS-CoV-2. In addition, we focus on virulence related to glucose-6-phosphate dehydrogenase deficiency (G6PDd), the most common human enzymopathy. Review of data on the response of individuals and communities with high prevalence of G6PDd to NP, prompts us to propose the rationale for a population-specific management approach to rationalize design of therapeutic interventions of SARS-CoV-2 infection, based on use of NP. This strategy may lead to personalized approaches and improve disease-related outcomes.

Time-series analysis of satellite-derived fine particulate matter pollution and asthma morbidity in Jackson, MS.

In order to examine associations between asthma morbidity and local ambient air pollution in an area with relatively low levels of pollution, we conducted a time-series analysis of asthma hospital admissions and fine particulate matter pollution (PM2.5) in and around Jackson, MS, for the period 2003 to 2011. Daily patient-level records were obtained from the Mississippi State Department of Health (MSDH) Asthma Surveillance System. Patient geolocations were aggregated into a grid with 0.1° × 0.1° resolution within the Jackson Metropolitan Statistical Area. Daily PM2.5 concentrations were estimated via machine-learning algorithms with remotely sensed aerosol optical depth and other associated parameters as inputs. Controlling for long-term temporal trends and meteorology, we estimated a 7.2% (95% confidence interval 1.7-13.1%) increase in daily all-age asthma emergency room admissions per 10 µg/m3 increase in the 3-day average of PM2.5 levels (current day and two prior days). Stratified analyses reveal significant associations between asthma and 3-day average PM2.5 for males and blacks. Our results contribute to the current epidemiologic evidence on the association between acute ambient air pollution exposure and asthma morbidity, even in an area characterized by relatively good air quality.

Malaria in Burkina Faso (West Africa) during the twenty-first century.

Temperature and rainfall predicted for the twenty-first century by global coupled models as reported by IPCC, (2014a, and b) were obtained regionally for Burkina Faso and through the Paluclim project, 2011-2014. One of the goals of this project was to assess the upcoming evolution of malaria transmission dynamics. From an impact model on malaria risk linked to climate variability, temperature and rainfall indices were derived. Malaria transmission dynamics were then predicted using the derived temperature and rainfall for the twenty-first century. Similar to the historical evidence of rainfall being an important factor for regulating the seasonal density of malaria vectors, this study also reports a definitive link between low-frequency rainfall variability and malaria in the region under the influence of the Atlantic Multidecadal Oscillation (AMO). This finding can be used by local stakeholders involved with the geography-based population health planning. Moreover, the predicted increase in temperature during the twenty-first century suggests a reduction of larvae survival in Burkina Faso and thus the malaria risk. More generally, the temperature increase could become a new limiting factor for malaria transmission dynamics in the Sahel Region (as reported by Mordecai et al. (2013).

The impact of preventive screening resource distribution on geographic and population-based disparities in colorectal cancer in Mississippi.

BACKGROUND: The state of Mississippi has the highest colorectal cancer (CRC) mortality rate in the USA. The geographic distribution of CRC screening resources and geographic- and population-based CRC characteristics in Mississippi are investigated to reveal the geographic disparity in CRC screening. METHODS: The primary practice sites of licensed gastroenterologists and the addresses of licensed medical facilities offering on-site colonoscopies were verified via telephone surveys, then these CRC screening resource data were geocoded and analyzed using Geographic Information Systems. Correlation analyses were performed to detect the strength of associations between CRC screening resources, CRC screening behavior and CRC outcome data. RESULTS: Age-adjusted colorectal cancer incidence rates, mortality rates, mortality-to-incidence ratios, and self-reported endoscopic screening rates from the years 2006 through 2010 were significantly different for Black and White Mississippians; Blacks fared worse than Whites in all categories throughout all nine Public Health Districts. CRC screening rates were negatively correlated with CRC incidence rates and CRC mortality rates. The availability of gastroenterologists varied tremendously throughout the state; regions with the poorest CRC outcomes tended to be underserved by gastroenterologists. CONCLUSIONS: Significant population-based and geographic disparities in CRC screening behaviors and CRC outcomes exist in Mississippi. The effects of CRC screening resources are related to CRC screening behaviors and outcomes at a regional level, whereas at the county level, socioeconomic factors are more strongly associated with CRC outcomes. Thus, effective control of CRC in rural states with high poverty levels requires both adequate preventive CRC screening capacity and a strategy to address fundamental causes of health care disparities.

The geographic distribution of mammography resources in Mississippi.

OBJECTIVE: To determine whether the availability of mammography resources affected breast cancer incidence rates, stage of disease at initial diagnosis, mortality rates and/or mortality-to-incidence ratios throughout Mississippi. METHODS: Mammography facilities were geocoded and the numbers of residents residing within a thirty minute drive of a mammography facility were calculated. Other data were extracted from the Mississippi Cancer Registry, the U.S. Census, and the Mississippi Behavioral Risk Factor Surveillance Survey (BRFSS). RESULTS & DISCUSSION: There were no statistically-significant differences between breast cancer incidence rates in Black versus White females in Mississippi; however, there were significant differences in the use of mammography, percentages of advanced-stage initial diagnoses, mortality rates, and mortality-to-incidence ratios, where Black females fared worse in each category. No statistically-significant correlations were observed between breast cancer outcomes and the availability of mammography facilities. The use of mammography was negatively correlated with advanced stage of disease at initial diagnosis. By combining Black and White subsets, a correlation between mammography use and improved survival was detected; this was not apparent in either subset alone. There was also a correlation between breast cancer mortality-to-incidence ratios and the percentage of the population living below the poverty level. CONCLUSIONS: The accessibility and use of mammography resources has a greater impact on breast cancer in Mississippi than does the geographic resource distribution per se. Therefore, intensified mammography campaigns to reduce the percentage of advanced-stage breast cancers initially diagnosed in Black women, especially in communities with high levels of poverty, are warranted in Mississippi.

Estimating the global abundance of ground level presence of particulate matter (PM2.5).

With the increasing awareness of the health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground level airborne particulate matter with a diameter of 2.5 microns or less (PM2.5). Here we use a suite of remote sensing and meteorological data products together with ground-based observations of particulate matter from 8,329 measurement sites in 55 countries taken 1997-2014 to train a machine-learning algorithm to estimate the daily distributions of PM2.5 from 1997 to the present. In this first paper of a series, we present the methodology and global average results from this period and demonstrate that the new PM2.5 data product can reliably represent global observations of PM2.5 for epidemiological studies.

GeoMedStat: an integrated spatial surveillance system to track air pollution and associated healthcare events.

Air pollutants, such as particulate matter with a diameter ≤2.5 microns (PM2.5) and ozone (O3), are known to exacerbate asthma and other respiratory diseases. An integrated surveillance system that tracks such air pollutants and associated disease incidence can assist in risk assessment, healthcare preparedness and public awareness. However, the implementation of such an integrated environmental health surveillance system is a challenge due to the disparate sources of many types of data and the implementation becomes even more complicated for a spatial and real-time system due to lack of standardised technological components and data incompatibility. In addition, accessing and utilising health data that are considered as Protected Health Information (PHI) require maintaining stringent protocols, which have to be supported by the system. This paper aims to illustrate the development of a spatial surveillance system (GeoMedStat) that is capable of tracking daily environmental pollutants along with both daily and historical patient encounter data. It utilises satellite data and the groundmonitor data from the US National Aeronautics and Space Administration (NASA) and the US Environemental Protection Agenecy (EPA), rspectively as inputs estimating air pollutants and is linked to hospital information systems for accessing chief complaints and disease classification codes. The components, developmental methods, functionality of GeoMedStat and its use as a real-time environmental health surveillance system for asthma and other respiratory syndromes in connection with with PM2.5 and ozone are described. It is expected that the framework presented will serve as an example to others developing real-time spatial surveillance systems for pollutants and hospital visits.

Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters.

The spread of dengue fever depends mainly on the availability of favourable breeding sites for its mosquito vectors around human dwellings. To investigate if the various factors influencing breeding habitats can be mapped from space, dengue indices, such as the container index, the house index and the Breteau index, were calculated from Ministry of Public health data collected three times annually in Phitsanulok, Thailand between 2009 and 2011. The most influential factors were found to be temperature, humidity, rainfall, population density, elevation and land cover. Models were worked out using parameters mostly derived from freely available satellite images and fuzzy logic software with parameter synchronisation and a predication algorithm based on data mining and the Decision Tree method. The models developed were found to be sufficiently flexible to accommodate additional parameters and sampling data that might improve prediction of favourable breeding hotspots. The algorithm applied can not only be used for the prediction of near real-time scenarios with respect to dengue, but can also be applied for monitoring other diseases influenced by environmental and climatic factors. The multi-criteria model presented is a cost-effective way of identifying outbreak hotspots and early warning systems lend themselves for development based on this strategy. The proposed approach demonstrates the successful utilisation of remotely sensed images to map mosquito breeding habitats.

Evolutionary trends in peer review.

The literature pertaining to the scientific peer-review process, which explains the history as well as the controversial debate over whether peer review truly enhances the quality of published studies, was reviewed. The strengths and weaknesses of peer review are summarized, and an overview of the possible future evolution of the practice is given. The studies that are included reflect a wide array of findings which both support and negate the practice. The implications are crucial for both authors and reviewers in the allied health sciences.

Methods for retrospective geocoding in population studies: the Jackson Heart Study.

The increasing use of geographic information systems (GIS) in epidemiological population studies requires careful attention to the methods employed in accomplishing geocoding and creating a GIS. Studies have provided limited details,hampering the ability to assess validity of spatial data. The purpose of this paper is to describe the multiphase geocoding methods used to retrospectively create a GIS in the Jackson Heart Study (JHS). We used baseline data from 5,302 participants enrolled in the JHS between 2000 and 2004 in a multiphase process to accomplish geocoding2 years after participant enrollment. After initial deletion of ungeocodable addresses(n=52), 96% were geocoded using ArcGIS. An interactive method using data abstraction from participant records, use of additional maps and street reference files,and verification of existence of address, yielded successful geocoding of all but 13 addresses. Overall, nearly 99% (n=5,237) of the JHS cohort was geocoded retrospectively using the multiple strategies for improving and locating geocodable addresses. Geocoding validation procedures revealed highly accurate and reliable geographic data. Using the methods and protocol developed provided a reliable spatial database that can be used for further investigation of spatial epidemiology. Baseline results were used to describe participants by select geographic indicators, including residence in urban or rural areas, as well as to validate the effectiveness of the study's sampling plan. Further, our results indicate that retrospectively developing a reliable GIS for a large, epidemiological study is feasible. This paper describes some of the challenges in retrospectively creating a GIS and provides practical tips that enhanced the success.

Use of hyperspectral imaging to distinguish normal, precancerous, and cancerous cells.

BACKGROUND: The objective of the current study was to test the hypothesis that the cytologic diagnosis of cancer cells can be enhanced by the technique of hyperspectral imaging (HSI). METHODS: As a proof of principle, HSI was employed to obtain hyperspectrum from a normal human fibroblast, as well as its telomerase-immortalized and SV40-transformed derivatives. Novel algorithms were developed to differentiate among these cell models based on spectral and spatial differences. Using the same technique with modified algorithms, the authors were able to differentiate among normal and precancerous (low-grade [LG] and high-grade [HG]) cervical cells and squamous cell carcinoma (SCC) on liquid-based Papanicolaou (Pap) test slides. RESULTS: The specificity for identifying normal fibroblast cell type based on spatial and spectral algorithms was 74.2%. The sensitivity for identifying telomerase-immortalized and SV40-transformed cells was 100% and 90.3%, respectively. The system identified normal cervical cells with a specificity of 95.8%. With regard to LG precancerous cells and HG precancerous cells, the sensitivity was 66.7% and 93.5%, respectively. The sensitivity detected for SCC was 98.6%. CONCLUSIONS: HSI can be utilized in prescreening liquid-based Pap test slides to improve efficiency in Pap test diagnoses with the goal of ultimately reducing the mortality from cervical cancer while reducing health care costs.

Assessment of arsenic contamination of groundwater and health problems in Bangladesh.

Excessive amounts of arsenic (As) in the groundwater in Bangladesh and neighboring states in India are a major public health problem. About 30% of the private wells in Bangladesh exhibit high concentrations of arsenic. Over half the country, 269 out of 464 administrative units, is affected. Similar problems exist in many other parts of the world, including the Unites States. This paper presents an assessment of the health hazards caused by arsenic contamination in the drinking water in Bangladesh. Four competing hypotheses, each addressing the sources, reaction mechanisms, pathways, and sinks of arsenic in groundwater, were analyzed in the context of the geologic history and land-use practices in the Bengal Basin. None of the hypotheses alone can explain the observed variability in arsenic concentration in time and space; each appears to have some validity on a local scale. Thus, it is likely that several biogeochemical processes are active among the region's various geologic environments, and that each contributes to the mobilization and release of arsenic. Additional research efforts will be needed to understand the relationships between underlying biogeochemical factors and the mechanisms for arsenic release in various geologic settings.

Breast cancer incidence and exposure to environmental chemicals in 82 counties in Mississippi.

OBJECTIVE: Breast cancer is a major public health problem in the United States and in most industrialized countries. Environmental exposure to several chemicals has been implicated in the cause of breast cancer. However, data are not consistent about the role of the environment in breast cancer incidence. To assess environmental risks for breast cancer, patterns of breast cancer incidence in relation to environmental chemicals in Mississippi counties were mapped. METHODS: This article presents an analysis of age-adjusted incidence rates of female breast cancer and environmental chemical emissions by county in the state of Mississippi. The incidence data were obtained from the State Department of Health, and emissions data sources included the U.S. Environmental Protection Agency's Air-Data and Toxics Release Inventory Program. RESULTS: Counties having a significantly higher incidence of breast cancer compared with the state's rate were identified. Also identified were counties with higher levels of chemical emissions. The incidence of breast cancer in 1998 was significantly associated with the amount of ammonia (r = 0.268, P = 0.015), minimum emissions (r = 0.233, P = 0.035), and maximum emissions (r = 0.237, P = 0.032) of the facilities in the county. A linear dose-response relationship was observed between increased amounts of chemical emissions and breast cancer incidence. CONCLUSIONS: This study found a significant link between breast cancer incidence and maximum emissions of environmental chemicals. However, further research using individual-level data is needed.