Exploring neighborhood inequality in female breast cancer incidence in Tehran using Bayesian spatial models and a spatial scan statistic

Evaluation and comparison of spatial cluster detection methods for improved decision making of disease surveillance: a case study of national dengue surveillance in Thailand

BACKGROUND

Dengue is a mosquito-borne disease that causes over 300 million infections worldwide each year with no specific treatment available. Effective surveillance systems are needed for outbreak detection and resource allocation. Spatial cluster detection methods are commonly used, but no general guidance exists on the most appropriate method for dengue surveillance. Therefore, a comprehensive study is needed to assess different methods and provide guidance for dengue surveillance programs.

METHODS

To evaluate the effectiveness of different cluster detection methods for dengue surveillance, we selected and assessed commonly used methods: Getis Ord [Formula: see text], Local Moran, SaTScan, and Bayesian modeling. We conducted a simulation study to compare their performance in detecting clusters, and applied all methods to a case study of dengue surveillance in Thailand in 2019 to further evaluate their practical utility.

RESULTS

In the simulation study, Getis Ord [Formula: see text] and Local Moran had similar performance, with most misdetections occurring at cluster boundaries and isolated hotspots. SaTScan showed better precision but was less effective at detecting inner outliers, although it performed well on large outbreaks. Bayesian convolution modeling had the highest overall precision in the simulation study. In the dengue case study in Thailand, Getis Ord [Formula: see text] and Local Moran missed most disease clusters, while SaTScan was mostly able to detect a large cluster. Bayesian disease mapping seemed to be the most effective, with adaptive detection of irregularly shaped disease anomalies.

CONCLUSIONS

Bayesian modeling showed to be the most effective method, demonstrating the best accuracy in adaptively identifying irregularly shaped disease anomalies. In contrast, SaTScan excelled in detecting large outbreaks and regular forms. This study provides empirical evidence for the selection of appropriate tools for dengue surveillance in Thailand, with potential applicability to other disease control programs in similar settings.

Breast cancer incidence in Yogyakarta, Indonesia from 2008-2019: A cross-sectional study using trend analysis and geographical information system

BACKGROUND

Breast cancer is a significant public health concern worldwide, including in Indonesia. Little is known about the spatial and temporal patterns of breast cancer incidence in Indonesia. This study aimed to analyze temporal and spatial variations of breast cancer incidence in Yogyakarta Province, Indonesia.

METHODS

The study used breast cancer case data from the Yogyakarta Population-Based Cancer Registry (PBCR) from 2008 to 2019. The catchment areas of the PBCR included the 48 subdistricts of 3 districts (Sleman, Yogyakarta City, and Bantul). Age-standardized incidence rates (ASR) were calculated for each subdistrict. Joinpoint regression was used to detect any significant changes in trends over time. Global Moran's and Local Indicators of Spatial Association (LISA) analyses were performed to identify any spatial clusters or outliers.

RESULTS

The subdistricts had a median ASR of 41.9, with a range of 15.3-70.4. The majority of cases were diagnosed at a late stage, with Yogyakarta City having the highest proportion of diagnoses at stage 4. The study observed a significant increasing trend in breast cancer incidence over the study period the fastest of which is in Yogyakarta City with an average annual percentage change of 18.77%, with Sleman having an 18.21% and Bantul having 8.94% average changes each year (p <0.05). We also found a significant positive spatial autocorrelation of breast cancer incidence rates in the province (I = 0.581, p <0.001). LISA analysis identified 11 subdistricts which were high-high clusters in the central area of Yogyakarta City and six low-low clusters in the southeast region of the catchment area in the Bantul and Sleman Districts. No spatial outliers were identified.

CONCLUSIONS

We found significant spatial clustering of BC ASR in the Yogyakarta Province, and there was a trend of increasing ASR across the region. These findings can inform resource allocation for public health efforts to high-risk areas and develop targeted prevention and early detection strategies. Further res is needed to understand the factors driving the observed temporal and spatial patterns of breast cancer incidence in Yogyakarta Province, Indonesia.

Clusters of high-risk, low-risk, and temporal trends of breast and cervical cancer-related mortality in São Paulo, Brazil, during 2000-2016

PURPOSE

Studying breast and cervical cancers in space and time and verifying divergences of different territorially established socioeconomic profiles.

METHODS

Ecological study using spatial scanning (with socioeconomic characterization), space-time, and spatial variation of temporal trends, in order to identify significant clusters of high- and low-risk or temporal trends, of deaths from breast cancer and cervical cancer, in the city of São Paulo, Brazil, during 2000-2016.

RESULTS

High-risk spatial clusters were identified in the central areas, and low-risk clusters were identified in the peripheral areas, which were associated with better and worse socioeconomic conditions, respectively. As for cervical cancer, the pattern was the opposite. High-risk space-time clusters occurred in the early years of the study, whereas low-risk clusters occurred in the most recent years. For breast cancer, the central areas showed a temporal trend of decreasing mortality and the peripheral areas showed an increasing trend. While for cervical cancer, in general, the temporal trend was for the identified clusters to fall.

CONCLUSIONS

It is expected that this study will provide insights for the formulation of public policies to implement prevention and control measures, in order to reduce mortality and inequalities related to breast and cervical cancers.

Intra-urban spatial variability of breast and cervical cancer mortality in the city of São Paulo: analysis of associated factors

OBJECTIVE

To identify spatial variability of mortality from breast and cervical cancer and to assess factors associated in the city of São Paulo.

METHODS

Between 2009 and 2016, 10,124 deaths from breast cancer and 2,116 deaths from cervical cancer were recorded in the Mortality Information System among women aged 20 years and over. The records were geocoded by address of residence and grouped according to Primary Health Care coverage areas. A spatial regression modeling was put together using the Bayesian approach with a Besag-York-Mollié structure to verify the association of deaths with selected indicators.

RESULTS

Mortality rates from these types of cancer showed inverse spatial patterns. These variables were associated with breast cancer mortality: travel time between one and two hours to work (RR - relative risk: 0.97; 95%CI - credible interval: 0.93-1.00); women being the head of the household (RR 0.97; 95%CI 0.94-0.99) and deaths from breast cancer in private health institutions (RR 1.04; 95%CI 1.00-1.07). The following variables were associated with mortality from cervical cancer: travel time to work between half an hour and one hour (RR 0.92; 95%CI 0.87-0.98); per capita household income of up to 3 minimum wages (RR 1.27; 95%CI 1.18-1.37) and ratio of children under one year of age related to the female population aged 15 to 49 years (RR 1.09; 95%CI 1.01-1.18).

CONCLUSION

The predicted RR for mortality from these cancers were calculated and associated with the socioeconomic conditions of the areas covered.

Intra-urban spatial variability of breast and cervical cancer mortality in the city of São Paulo: analysis of associated factors

ABSTRACT Objective: To identify spatial variability of mortality from breast and cervical cancer and to assess factors associated in the city of São Paulo. Methods: Between 2009 and 2016, 10,124 deaths from breast cancer and 2,116 deaths from cervical cancer were recorded in the Mortality Information System among women aged 20 years and over. The records were geocoded by address of residence and grouped according to Primary Health Care coverage areas. A spatial regression modeling was put together using the Bayesian approach with a Besag-York-Mollié structure to verify the association of deaths with selected indicators. Results: Mortality rates from these types of cancer showed inverse spatial patterns. These variables were associated with breast cancer mortality: travel time between one and two hours to work (RR – relative risk: 0.97; 95%CI – credible interval: 0.93–1.00); women being the head of the household (RR 0.97; 95%CI 0.94–0.99) and deaths from breast cancer in private health institutions (RR 1.04; 95%CI 1.00–1.07). The following variables were associated with mortality from cervical cancer: travel time to work between half an hour and one hour (RR 0.92; 95%CI 0.87–0.98); per capita household income of up to 3 minimum wages (RR 1.27; 95%CI 1.18–1.37) and ratio of children under one year of age related to the female population aged 15 to 49 years (RR 1.09; 95%CI 1.01–1.18). Conclusion: The predicted RR for mortality from these cancers were calculated and associated with the socioeconomic conditions of the areas covered.

The Effect of Religious-Spiritual Psychotherapy on Illness Perception and Inner Strength among Patients with Breast Cancer in Iran

Women diagnosed with breast cancer often suffer from illness-related issues, which negatively impact their illness perception and inner strength following diagnosis and/or during treatment. An investigation of the effectiveness of religious-spiritual psychotherapy based on the Twelver Shia Sects of Islam (RSP-TSS) was conducted among hospitalized cancer patients to determine whether it improved their disease perception and inner strength. Forty-five women (ages 31-58) diagnosed with breast cancer in Iran were randomly assigned to RSP-TSS (n = 15), attention control (n = 15) and untreated control groups (n = 15). To meet the needs of hospitalized participants, the manualized RSP-TSS protocol was adapted to consist of ten sessions, each lasting 90 min. Sessions were conducted once weekly for 10 weeks. Primary outcome measures were the Revised Illness Perception Questionnaire (IPQ-R) and the Inner Strength Questionnaire (ISQ). Data were collected in pre-intervention, post-intervention, and 4 months following the intervention. Repeated MANOVA measures showed that, as compared with the attention control and untreated control groups, the RSP-TSS group achieved significant improvements in illness perception and inner strengths, and those gains were maintained during the 4-month follow-up. By reframing illness perception and building inner strength, spiritual and religious-based interventions may improve patients coping with cancer and improve the quality of life for women hospitalized with breast cancer. These promising results warrant further investigation into the efficacy of spiritual and religious-based interventions to remediate illness perception and inner strength problems in women diagnosed with serious medical illnesses.

Campania and cancer mortality: An inseparable pair? The role of environmental quality and socio-economic deprivation

The region of Campania in Southern Italy features high levels of socio-economic deprivation and low levels of environmental quality. A vast strand of the scientific literature has tried to verify whether poor environmental quality and widespread socio-economic deprivation might explain the high cancer mortality rates (CMRs) observed, especially in the municipalities - infamously labelled as the 'Land of Fires' - that were hit most severely by the crisis. While some studies managed to identify links between these two confounding factors and cancer mortality, the evidence is overall mixed. Interesting information may be drawn from the observation of municipal data: in spite of previous claims, some municipalities featuring high environmental quality and low socio-economic deprivation also display high CMRs, while other Campanian municipalities facing disastrous environmental and socio-economic conditions are characterised by low CMRs. These figures, in contrast to common sentiment and previous studies, need to be investigated thoroughly in order to assess the exact role of the confounding factors. In this work, we aim to identify the municipalities where confounding factors act as driving forces in the determination of high CMRs through an original multi-step analysis based on frequentist and Bayesian analysis. Pinpointing these municipalities could allow policymakers to design targeted and effective policy measures aimed at reducing cancer mortality.

Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models

BACKGROUND

Saskatchewan has one of the highest incidence of prostate cancer (PCa) in Canada. This study assesses if geographic factors in Saskatchewan, including location of where patients live and physician density are affecting the PCa incidence. First, the objective of this study is to estimate the PCa standardized incidence ratio (SIRs) in Saskatchewan stratified by PCa risk-level. Second, this study identifies clusters of higher than and lower than expected PCa SIRs in Saskatchewan. Lastly, this study identifies the association (if any) between family physician density and estimated PCa SIRs in Saskatchewan.

METHODS

First, using Global Moran's I, Local Moran's I, and the Kuldorff's Spatial Scan Statistic, the study identifies clusters of PCa stratified by risk-levels. Then this study estimates the SIRs of PCa and its association with family physician density in Saskatchewan using the Besag, York, and Mollie (BYM) Bayesian method.

RESULTS

Higher than expected clusters of crude estimated SIR for metastatic PCa were identified in north-east Saskatchewan and lower than expected clusters were identified in south-east Saskatchewan. Areas in north-west Saskatchewan have lower than expected crude estimated SIRs for both intermediate-risk and low-risk PCa. Family physician density was negatively associated with SIRs of metastatic PCa (IRR: 0.935 [CrI: 0.880 to 0.998]) and SIRs of high-risk PCa (IRR: 0.927 [CrI: 0.880 to 0.975]).

CONCLUSIONS

This study identifies the geographical disparities in risk-stratified PCa incidence in Saskatchewan. The study identifies areas with a lower family physician density have a higher-than-expected incidences of metastatic and high-risk PCa. Hence policies to increase the number of physicians should ensure an equitable geographic distribution of primary care physicians to support early detection of diseases, including PCa.

A Multi-Decadal Spatial Analysis of Demographic Vulnerability to Urban Flood: A Case Study of Birmingham City, USA

Flooding, including hurricanes and tornadoes, accounts for approximately 40 percent of natural disasters worldwide and kills 100 people on average in the United States each year, which is more than any other single weather hazard. Since flooding is a common hazard in the U.S. and flood-related casualties have been increasing in recent years, it is important to understand the spatial patterns of different vulnerable population groups in the flooding regions. To achieve this objective, spatial scan statistics were used to identify the spatial clusters of different demographic groups (children and elderly, poor, White, African American, and Hispanic) in the 100-year floodplain areas of Birmingham. Using the decennial census data from 1990 to 2015, this research examined whether these vulnerable population groups had aggregated more in the flooding areas or moved away from the flooding areas in the past thirty years. The findings of this research indicate that most of the minorities are increasingly aggregating in the floodplain areas of Village Creek in Birmingham. The findings also suggest that the non-minorities are moving away from the flooding regions in Birmingham, AL. As part of the minorities and non-minorities group, approximately 50 percent of African Americans and 4 percent of White populations aggregated in the Village Creek flooding areas in 2015. Although the percentage of White populations is very low, the findings suggest that they are still exposed to floods. The multi-decadal analysis of flood risk will help the local governments to understand which population groups could be more affected by floods historically and need more attention in future flood hazards. This understanding will help them prepare for future flood hazards by allocating resources efficiently among the different racial and ethnic groups.

Cancer mortality rates and spillover effects among different areas: A case study in Campania (southern Italy)

The present study analyses the spatial distribution of cancer mortality rates in Campania (an Italian region with the highest population density), in which residents in several areas are exposed to major environmental health hazards. The paper has the methodological aims of verifying the existence, or otherwise, of a spatial correlation between mortality from different types of cancer and the occurrence of some specific area characteristics, using both Bayesian statistics and spatial econometrics. We show that the use of the Spatial Empirical Bayes Smoothed Rate, instead of the more commonly used Raw Rate, allows a more comprehensive analysis of the mortality rate, highlighting the existence of different cluster sizes throughout the region, according to the type of cancer mortality rate analysed. By using a Spatial Durbin model we verify that cancer mortality rates are related to the environmental characteristics of specific areas with spatial spillover effects. Our results validate the hypothesis that living along the coast by Mt Vesuvius and, to a lesser extent, along the Domitio-Flegreo coast NW of Naples and in more urbanised municipalities, increases the risk of dying of cancer. By contrast, living in less urbanised municipalities, with the presence of natural and historical attractions, has a positive effect on the residents' health, reducing their risk of disease. In both cases significant spillover effects (negative and positive) are found in municipalities close to the areas in question. Despite a number of reasonable limitations, our findings may provide useful information support for policy makers to foster knowledge, awareness and informed participation of citizens.

Spatial modeling of cutaneous leishmaniasis in Iranian army units during 2014-2017 using a hierarchical Bayesian method and the spatial scan statistic

OBJECTIVES

This study aimed to map the incidence of cutaneous leishmaniasis (CL) in Iranian army units (IAUs) and to identify possible spatial clusters.

METHODS

This ecological study investigated incident cases of CL between 2014 and 2017. CL data were extracted from the CL registry maintained by the deputy of health of AJA University of Medical Sciences. The standardized incidence ratio (SIR) of CL was computed with a Besag, York, and Mollié model. The purely spatial scan statistic was employed to detect the most likely highand low-rate clusters and to obtain the observed-to-expected (O/E) ratio for each detected cluster. The statistical significance of the clusters was assessed using the log likelihood ratio (LLR) test and Monte Carlo hypothesis testing.

RESULTS

A total of 1,144 new CL cases occurred in IAUs from 2014 to 2017, with an incidence rate of 260 per 100,000. Isfahan and Khuzestan Provinces were found to have more CL cases than expected in all studied years (SIR>1), while Kermanshah, Kerman, and Fars Provinces were observed to have been high-risk areas in only some years of the study period. The most significant CL cluster was in Kermanshah Province (O/E, 67.88; LLR, 1,200.62; p<0.001), followed by clusters in Isfahan Province (O/E, 6.02; LLR, 513.24; p<0.001) and Khuzestan Province (O/E, 2.35; LLR, 73.71; p<0.001), while low-rate clusters were located in the northeast areas, including Razavi Khorasan, North Khorasan, Semnan, and Golestan Provinces (O/E, 0.03; LLR, 95.11; p<0.001).

CONCLUSIONS

This study identified high-risk areas for CL. These findings have public health implications and should be considered when planning control interventions among IAUs.