Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016-2021.

BACKGROUND: Ghana is among the top 10 highest malaria burden countries, with about 20,000 children dying annually, 25% of which were under five years. This study aimed to produce interactive web-based disease spatial maps and identify the high-burden malaria districts in Ghana. METHODS: The study used 2016-2021 data extracted from the routine health service nationally representative and comprehensive District Health Information Management System II (DHIMS2) implemented by the Ghana Health Service. Bayesian geospatial modelling and interactive web-based spatial disease mapping methods were employed to quantify spatial variations and clustering in malaria risk across 260 districts. For each district, the study simultaneously mapped the observed malaria counts, district name, standardized incidence rate, and predicted relative risk and their associated standard errors using interactive web-based visualization methods. RESULTS: A total of 32,659,240 malaria cases were reported among children < 5 years from 2016 to 2021. For every 10% increase in the number of children, malaria risk increased by 0.039 (log-mean 0.95, 95% credible interval = - 13.82-15.73) and for every 10% increase in the number of males, malaria risk decreased by 0.075, albeit not statistically significant (log-mean - 1.82, 95% credible interval = - 16.59-12.95). The study found substantial spatial and temporal differences in malaria risk across the 260 districts. The predicted national relative risk was 1.25 (95% credible interval = 1.23, 1.27). The malaria risk is relatively the same over the entire year. However, a slightly higher relative risk was recorded in 2019 while in 2021, residing in Keta, Abuakwa South, Jomoro, Ahafo Ano South East, Tain, Nanumba North, and Tatale Sanguli districts was associated with the highest malaria risk ranging from a relative risk of 3.00 to 4.83. The district-level spatial patterns of malaria risks changed over time. CONCLUSION: This study identified high malaria risk districts in Ghana where urgent and targeted control efforts are required. Noticeable changes were also observed in malaria risk for certain districts over some periods in the study. The findings provide an effective, actionable tool to arm policymakers and programme managers in their efforts to reduce malaria risk and its associated morbidity and mortality in line with the Sustainable Development Goals (SDG) 3.2 for limited public health resource settings, where universal intervention across all districts is practically impossible.

Evaluating Methods for Mapping Historical Redlining to Census Tracts for Health Equity Research.

Neighborhood characteristics including housing status can profoundly influence health. Recently, increasing attention has been paid to present-day impacts of "redlining," or historic area classifications that indicated less desirable (redlined) areas subject to decreased investment. Scholarship of redlining and health is emerging; limited guidance exists regarding optimal approaches to measuring historic redlining in studies of present-day health outcomes. We evaluated how different redlining approaches (map alignment methods) influence associations between redlining and health outcomes. We first identified 11 existing redlining map alignment methods and their 37 logical extensions, then merged these 48 map alignment methods with census tract life expectancy data to construct 9696 linear models of each method and life expectancy for all 202 redlined cities. We evaluated each model's statistical significance and R2 values and compared changes between historical and contemporary geographies and populations using Root Mean Squared Error (RMSE). RMSE peaked with a normal distribution at 0.175, indicating persistent difference between historical and contemporary geographies and populations. Continuous methods with low thresholds provided higher neighborhood coverage. Weighting methods had more significant associations, while high threshold methods had higher R2 values. In light of these findings, we recommend continuous methods that consider contemporary population distributions and mapping overlap for studies of redlining and health. We developed an R application {holcmapr} to enable map alignment method comparison and easier method selection.

Modernizing the design and analysis of prevalence surveys for neglected tropical diseases.

Current WHO guidelines set prevalence thresholds below which a neglected tropical disease can be considered to have been eliminated as a public health problem, and specify how surveys to assess whether elimination has been achieved should be designed and analysed, based on classical survey sampling methods. In this paper, we describe an alternative approach based on geospatial statistical modelling. We first show the gains in efficiency that can be obtained by exploiting any spatial correlation in the underlying prevalence. We then suggest that the current guidelines' implicit use of a significance testing argument is not appropriate; instead, we argue for a predictive inferential framework, leading to design criteria based on controlling the rates at which areas whose true prevalence lies above and below the elimination threshold are incorrectly classified. We describe how this approach naturally accommodates context-specific information in the form of georeferenced covariates that have been shown to be predictive of disease prevalence. Finally, we give a progress report of an ongoing collaboration with the Guyana Ministry of Health Neglected Tropical Disease programme on the design of an IDA (ivermectin, diethylcarbamazine and albendazole) Impact Survey of lymphatic filariasis to be conducted in Guyana in early 2023. This article is part of the theme issue 'Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.

Dataset of urban development analysis in a section of Kuje Area Council, Abuja, Nigeria.

Urban development will likely continue to increase in suburban areas to cater for the growing human population. In Nigeria, the relevant analysis of these urban developments is not well documented. This article presents spatiotemporal datasets for analysing urban developments in a suburb of Kuje, an Area Council within the Federal Capital Territory of Nigeria. Data from Google Earth (GE) historical imagery of 2005 was used as a baseline for analysis and was compared with a UAV digital orthomosaic of 2019 to quantify urban developments. This data provides useful information on the status of urban development that has taken place in the Kuje suburb over 14 years. The data will be of great importance to town planners and urban development authorities for future planning, and for making informed decisions about urban development issues in the area.

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web-based mapping methods.

BACKGROUND: Under-five child malaria is one of the leading causes of morbidity and mortality globally, especially among sub-Saharan African countries like Ghana. In Ghana, malaria is responsible for about 20,000 deaths in children annually of which 25% are those aged < 5 years. To provide opportunities for efficient malaria surveillance and targeted control efforts amidst limited public health resources, the study produced high resolution interactive web-based spatial maps that characterized geographical differences in malaria risk and identified high burden communities. METHODS: This modelling and web-based mapping study utilized data from the 2019 Malaria Indicators Survey (MIS) of the Demographic and Health Survey Program. A novel and advanced Bayesian geospatial modelling and mapping approaches were utilized to examine predictors and geographical differences in under-five malaria. The model was validated via a cross-validation approach. The study produced an interactive web-based visualization map of the malaria risk by mapping the predicted malaria prevalence at both sampled and unsampled locations. RESULTS: In 2019, 718 (25%) of 2867 under-five children surveyed had malaria. Substantial geographical differences in under-five malaria risk were observed. ITN coverage (log-odds 4.5643, 95% credible interval = 2.4086-6.8874), travel time (log-odds 0.0057, 95% credible interval = 0.0017-0.0099) and aridity (log-odds = 0.0600, credible interval = 0.0079-0.1167) were predictive of under-five malaria in the spatial model. The overall predicted national malaria prevalence was 16.3% (standard error (SE) 8.9%) with a range of 0.7% to 51.4% in the spatial model with covariates and prevalence of 28.0% (SE 13.9%) with a range of 2.4 to 67.2% in the spatial model without covariates. Residing in parts of Central and Bono East regions was associated with the highest risk of under-five malaria after adjusting for the selected covariates. CONCLUSION: The high-resolution interactive web-based predictive maps can be used as an effective tool in the identification of communities that require urgent and targeted interventions by programme managers and implementers. This is key as part of an overall strategy in reducing the under-five malaria burden and its associated morbidity and mortality in a country with limited public health resources where universal intervention is practically impossible.

Aging in the downtown corridor: Mapping the neighborhood experiences of Seattle's unhoused adults over age 50.

Research has established the importance of understanding the dynamic relationship between older adults and the environments in which they are embedded. However, the meaning of place for unhoused older adults amidst an increasingly contested urban landscape is largely unknown. This exploratory study aims to further include unhoused older adults' experiences in the scholarship on aging and place by asking how unhoused adults over age 50 (1) describe their spatial patterns and experiences and (2) negotiate their relationship with common urban places. Through iterative mapping conducted in focus groups and interviews at Seattle senior centers, respondents identified how they interacted with their communities and environment. Using inductive and deductive coding of both textual and geospatial data, thematic analysis indicated that respondents: (1) experienced confinement to the downtown corridor and expulsion from surrounding areas- a phenomenon compounded by physical and subjective aging; (2) created routines amidst geographic and temporal restrictions to maximize comfort and security; (3) attempted to create residential normalcy in public places through adaptive and accommodative practices; and (4) experienced identities shaped by movement through and access to place. Current social, spatial, and political contexts of city living present many challenges for older unhoused adults. Supports that ignore people's identification with the places that are important to them are unlikely to be successful. Findings from this paper call for service, policy, and design strategies that facilitate personal agency and connection to place among unhoused people midlife and beyond.

Geographic hotspot detection for late-stage hepatocellular carcinoma: novel approach to cancer control.

IMPORTANCE: As hepatocellular carcinoma (HCC)-associated mortality continues to rise in the United States, there is a crucial need for strategies to shift diagnoses from late to early stage in order to improve survival. OBJECTIVE: To describe a population-based geospatial approach to identifying areas with high late-stage HCC burden for intervention. DESIGN: Cross-sectional study between 2008 and 2017. SETTING: Los Angeles County. PARTICIPANTS: All incident cases of HCC with residential address at diagnosis in Los Angeles County were identified from a population-based cancer registry. Late stage included AJCC 7th Edition stages III-IV and unstaged cases. EXPOSURE: Sociodemographic factors. MAIN OUTCOME(S): Geographic "hotspots" or areas with a high density of late-stage HCC, identified using kernel density estimation in ArcMap 10.3.1. RESULTS: 51.8% of 7,519 incident cases of HCC were late stage. We identified a total of 23 late-stage hotspots, including 30.0% of all late-stage cases. Cases within hotspots were more often racial/ethnic minorities, foreign-born, under or uninsured, and of lower socioeconomic status. The age-adjusted incidence rate of late-stage HCC was twofold higher within hotspots (6.85 per 100,000 in hotspots vs 3.38 per 100,000 outside of hotspots). The calculated population-attributable risk was 43%, suggesting that a substantial proportion of late-stage HCC burden could be averted by introducing interventions in hotspot areas. We mapped the relationship between hotspots and federally qualified health centers primary care clinics and subspecialty clinics in Los Angeles County to demonstrate how clinic partnerships can be selected to maximize impact of interventions and resource use. Hotspots can also be utilized to identify "high-risk" neighborhoods that are easily recognizable by patients and the public and to facilitate community partnerships. CONCLUSION AND RELEVANCE: Reducing late-stage HCC through geographic late-stage hotspots may be an efficient approach to improving cancer control and equity.

A geospatial examination of specialist care accessibility and impact on health outcomes for patients with acute traumatic spinal cord injury in New South Wales, Australia: a population record linkage study.

BACKGROUND: Timely treatment is essential for achieving optimal outcomes after traumatic spinal cord injury (TSCI), and expeditious transfer to a specialist spinal cord injury unit (SCIU) is recommended within 24 h from injury. Previous research in New South Wales (NSW) found only 57% of TSCI patients were admitted to SCIU for acute post-injury care; 73% transferred within 24 h from injury. We evaluated pre-hospital and inter-hospital transfer practices to better understand the post-injury care pathways impact on patient outcomes and highlight areas in the health service pathway that may benefit from improvement. METHODS: This record linkage study included administrative pre-hospital (Ambulance), admissions (Admitted Patients) and costs data obtained from the Centre for Health Record Linkage, NSW. All patients aged ≥16 years with incident TSCI in NSW (2013-2016) were included. We investigated impacts of geographical disparities on pre-hospital and inter-hospital transport decisions from injury location using geospatial methods. Outcomes assessed included time to SCIU, surgery and the impact of these variables on the experience of inpatient complications. RESULTS: Inclusion criteria identified 316 patients, geospatial analysis showed that over half (53%, n = 168) of all patients were injured within 60 min road travel of a SCIU, yet only 28.6% (n = 48) were directly transferred to a SCIU. Patients were more likely to experience direct transfer to a SCIU without comorbid trauma (p < 0.01) but higher ICISS (p < 0.001), cervical injury (p < 0.01), and transferred by air-ambulance (p < 0.01). Indirect transfer to SCIU was more likely with two or more additional traumatic injuries (p < 0.01) or incomplete injury (p < 0.01). Patients not admitted to SCIU at all were older (p = 0.05) with lower levels of injury (p < 0.01). Direct transfers received earlier operative intervention (median (IQR) 12.9(7.9) hours), compared with patients transferred indirectly to SCIU (median (IQR) 19.5(18.9) hours), and had lower risk of complications (OR 3.2 v 1.4, p < 0.001). Complications included pressure injury, deep vein thrombosis, urinary infection, among others. CONCLUSIONS: Getting patients with acute TSCI patients to the right place at the right time is dependent on numerous factors; some are still being triaged directly to non-trauma services which delays specialist and surgical care and increases complication risks. The higher rates of complication following delayed transfer to a SCIU should motivate health service policy makers to investigate reasons for this practice and consent to improvement strategies. More stringent adherence to recommended guidelines would prioritise direct SCIU transfer for patients injured within 60 min radius, enabling the benefits of specialised care.

Rethinking neglected tropical disease prevalence survey design and analysis: a geospatial paradigm.

Current methods for the design and analysis of neglected tropical disease prevalence surveys largely rely on classical survey sampling ideas that treat prevalence data from different locations as an independent random sample from the probability distribution induced by a random sampling design. We set out an alternative, explicitly geospatial paradigm that can deliver much more precise estimates of the geospatial variation in prevalence over a country or region of interest. We describe the advantages of this approach under three headings: streamlining, whereby more precise results can be obtained with smaller sample sizes; integrating, whereby a joint analysis of data from two or more diseases can bring further gains in precision; and adapting, whereby the choice of future sampling location is informed by past data.

Using Web-Based Pin-Drop Maps to Capture Activity Spaces Among Young Adults Who Use Drugs in Rural Areas: Cross-Sectional Survey.

BACKGROUND: Epicenters of harmful drug use are expanding to US rural areas, with rural young adults bearing a disproportionate burden. A large body of work suggests that place characteristics (eg, spatial access to health services) shape vulnerability to drug-related harms among urban residents. Research on the role of place characteristics in shaping these harms among rural residents is nascent, as are methods of gathering place-based data. OBJECTIVE: We (1) analyzed whether young rural adults who used drugs answered self-administered Web-based mapping items about locations where they engaged in risk behaviors and (2) determined the precision of mapped locations. METHODS: Eligible individuals had to report recently using opioids to get high; be aged between 18 and 35 years; and live in the 5-county rural Appalachian Kentucky study area. We used targeted outreach and peer-referral methods to recruit participants. The survey asked participants to drop a pin in interactive maps to mark where they completed the survey, and where they had slept most; used drugs most; and had sex most in the past 6 months. Precision was assessed by (1) determining whether mapped locations were within 100 m of a structure and (2) calculating the Euclidean distance between the pin-drop home location and the street address where participants reported sleeping most often. Measures of central tendency and dispersion were calculated for all variables; distributions of missingness for mapping items and for the Euclidean distance variable were explored across participant characteristics. RESULTS: Of the 151 participants, 88.7% (134/151) completed all mapping items, and ≥92.1% (>139/151) dropped a pin at each of the 4 locations queried. Missingness did not vary across most participant characteristics, except that lower percentages of full-time workers and peer-recruited participants mapped some locations. Two-thirds of the pin-drop sex and drug use locations were less than 100 m from a structure, as were 92.1% (139/151) of pin-drop home locations. The median distance between the pin-drop and street-address home locations was 2.0 miles (25th percentile=0.8 miles; 75th percentile=5.5 miles); distances were shorter for high-school graduates, staff-recruited participants, and participants reporting no technical difficulties completing the survey. CONCLUSIONS: Missingness for mapping items was low and unlikely to introduce bias, given that it varied across few participant characteristics. Precision results were mixed. In a rural study area of 1378 square miles, most pin-drop home addresses were near a structure; it is unsurprising that fewer drug and sex locations were near structures because most participants reported engaging in these activities outside at times. The error in pin-drop home locations, however, might be too large for some purposes. We offer several recommendations to strengthen future research, including gathering metadata on the extent to which participants zoom in on each map and recruiting participants via trusted staff.

Geo-epidemiologic mapping in the new public health surveillance. The malaria case in Chiapas, Mexico, 2002. / Mapeo geoepidemiológico en la nueva vigilancia de salud pública. El caso de la malaria en Chiapas, México, en 2002.

The new public health surveillance requires at the global, national and local levels the use of new authoritative analytical approaches and tools for better recognition of the epidemiologic characteristics of the priority health events and risk factors affecting the population health. The identification of the events in time and space is of fundamental importance so that the geo-spatial description of the situation of diseases and health events facilitates the identification of social, environmental and health care related risks. This assessment examines the application and use of geo-spatial tools for identifying relevant spatial and epidemiological conglomerates of malaria in Chiapas, Mexico. The study design was ecological and the level of aggregation of the collected information of the epidemiological and spatial variables was municipalities. The data were collected in all municipalities of the state of Chiapas, Mexico during the years 2000-2002. The main outcome variable was cases and types of malaria diagnosed by blood smears in weekly reports. Independent variables were age, sex, ethnicity, literacy of the cases of malaria and environmental factors such as altitude, road type and network in the municipalities and cities of Chiapas. The production of thematic maps and the application of geo-spatial analytical tools such Moran and local indicator of spatial autocorrelation metrics for malaria clustering allowed the visualization and recognition that the important population risk factors associated with high malaria incidence in Chiapas were low literacy rate, areas with high percentage of indigenous population that reflects the social inequalities gaps in health and the great burden of disease that is affecting this important vulnerable group in Chiapas. The presence of road networks allowed greater spatial diffusion of Malaria. An important epidemiological and spatial cluster of malaria was identified in the areas and populations in the proximity of the southern border. The use of geospatial metrics in local areas will assist in the epidemiological stratification of malaria for better targeting more effective and equitable prevention and control interventions.