Looking Back, Looking Forward: Progress and Prospect for Spatial Demography

In 2011 a specialist meeting on the “Future Directions in Spatial Demography” was held in Santa Barbara, California (Matthews, Goodchild, & Janelle, 2012).1 This specialist meeting was the capstone to a multi-year National Institutes of Health training grant that had supported workshops in advanced spatial analysis methods increasing used by population scientists.2 Early-career scholars who had participated in the training workshops and senior demographers and geographers drawn from across the United States participated in the specialist meeting.3 The application process to attend the 2011 meeting, required that each of the forty-one attendees submit a statement that reviewed challenges and identifed new directions for spatial demography, including gaps in current knowledge regarding innovations in geospatial data, spatial statistical methods, and the integration of data and models to enhance the science of spatial demography in population and health research. Reading again some of the ruminations of these scholars is an interesting exercise in its own right. The level of optimism back in 2011 was high, and especially regarding anticipated changes in computational capacity, leveraging big data (including volunteered geographic information), developments in data systems (including new data high resolution data products and online resources such as multi-scale map interfaces and dashboards), and in methods such as time–space models, agent-based models, microsimulation, and small-area estimation. There were also several challenges identifed including, but not limited to, study designs, data integration, data validation, confdentiality, non-representative data, historic data, defnitions of place, residential selection and mobility as well as two overarching challenges related to the role and contribution of spatial demographers in interdisciplinary population and health research, and many, many comments on training issues. Substantively the attendees research focused on all forms of interaction between people and place (and the reciprocal relations between the people in social, built, and physical environment contexts) covering the gamut of demographic processes from reproductive health to mortality, though with perhaps an overrepresentation of researchers in areas related to population and environment research, racial and residential segregation, and migration.The R25 Training Grant was funded through the Eunice Kennedy Shriver National Institutes of Child Health and Human Development (NICHD 5R-25 HD057002; Principal Investigator: Stephen A. Matthews).

Looking Back, Looking Forward: Progress and Prospect for Spatial Demography

In 2011 a specialist meeting on the “Future Directions in Spatial Demography” was held in Santa Barbara, California (Matthews, Goodchild, & Janelle, 2012).1 This specialist meeting was the capstone to a multi-year National Institutes of Health training grant that had supported workshops in advanced spatial analysis methods increasing used by population scientists.2 Early-career scholars who had participated in the training workshops and senior demographers and geographers drawn from across the United States participated in the specialist meeting.3 The application process to attend the 2011 meeting, required that each of the forty-one attendees submit a statement that reviewed challenges and identifed new directions for spatial demography, including gaps in current knowledge regarding innovations in geospatial data, spatial statistical methods, and the integration of data and models to enhance the science of spatial demography in population and health research. Reading again some of the ruminations of these scholars is an interesting exercise in its own right. The level of optimism back in 2011 was high, and especially regarding anticipated changes in computational capacity, leveraging big data (including volunteered geographic information), developments in data systems (including new data high resolution data products and online resources such as multi-scale map interfaces and dashboards), and in methods such as time–space models, agent-based models, microsimulation, and small-area estimation. There were also several challenges identifed including, but not limited to, study designs, data integration, data validation, confdentiality, non-representative data, historic data, defnitions of place, residential selection and mobility as well as two overarching challenges related to the role and contribution of spatial demographers in interdisciplinary population and health research, and many, many comments on training issues. Substantively the attendees research focused on all forms of interaction between people and place (and the reciprocal relations between the people in social, built, and physical environment contexts) covering the gamut of demographic processes from reproductive health to mortality, though with perhaps an overrepresentation of researchers in areas related to population and environment research, racial and residential segregation, and migration.The R25 Training Grant was funded through the Eunice Kennedy Shriver National Institutes of Child Health and Human Development (NICHD 5R-25 HD057002; Principal Investigator: Stephen A. Matthews).

Temporal Variations and Spatial Clusters of Dengue in Thailand: Longitudinal Study before and during the Coronavirus Disease (COVID-19) Pandemic

The efforts towards effective control of the COVID-19 pandemic may affect the incidence of dengue. This study aimed to investigate temporal variations and spatial clusters of dengue in Thailand before and during the COVID-19 pandemic. Reported dengue cases before (2011–2019) and during (2020–2021) the COVID-19 pandemic were obtained from the national disease surveillance datasets. The temporal variations were analyzed using graphics, a seasonal trend decomposition procedure based on Loess, and Poisson regression. A seasonal ARIMA model was used to forecast dengue cases. Spatial clusters were investigated using the local indicators of spatial associations (LISA). The cyclic pattern showed that the greatest peak of dengue cases likely changed from every other year to every two or three years. In terms of seasonality, a notable peak was observed in June before the pandemic, which was delayed by one month (July) during the pandemic. The trend for 2011–2021 was relatively stable but dengue incidence decreased dramatically by 7.05% and 157.80% on average in 2020 and 2021, respectively. The forecasted cases in 2020 were slightly lower than the reported cases (2.63% difference), whereas the forecasted cases in 2021 were much higher than the actual cases (163.19% difference). The LISA map indicated 5 to 13 risk areas or hotspots of dengue before the COVID-19 pandemic compared to only 1 risk area during the pandemic. During the COVID-19 pandemic, dengue incidence sharply decreased and was lower than forecasted, and the spatial clusters were much lower than before the pandemic

Human population movement and behavioural patterns in malaria hotspots on the Thai-Myanmar border: implications for malaria elimination.

BackgroundMalaria is heterogeneously distributed across landscapes. Human population movement (HPM) could link sub-regions with varying levels of transmission, leading to the persistence of disease even in very low transmission settings. Malaria along the Thai-Myanmar border has been decreasing, but remains heterogeneous. This study aimed to measure HPM, associated predictors of travel, and HPM correlates of self-reported malaria among people living within malaria hotspots.Methods526 individuals from 279 households in two malaria hotspot areas were included in a prospective observational study. A baseline cross-sectional study was conducted at the beginning, recording both individual- and household-level characteristics. Individual movement and travel patterns were repeatedly observed over one dry season month (March) and one wet season month (May). Descriptive statistics, random effects logistic regressions, and logistic regressions were used to describe and determine associations between HPM patterns, individual-, household-factors, and self-reported malaria.ResultsTrips were more common in the dry season. Malaria risk was related to the number of days doing outdoor activities in the dry season, especially trips to Myanmar, to forest areas, and overnight trips. Trips to visit forest areas were more common among participants aged 20-39, males, individuals with low income, low education, and especially among individuals with forest-related occupations. Overnight trips were more common among males, and individual with forest-related occupations. Forty-five participants reported having confirmed malaria infection within the last year. The main place of malaria blood examination and treatment was malaria post and malaria clinic, with participants usually waiting for 2-3 days from onset fever to seeking diagnosis. Individuals using bed nets, living in houses with elevated floors, and houses that received indoor residual spraying in the last year were less likely to report malaria infection.ConclusionAn understanding of HPM and concurrent malaria dynamics is important for consideration of targeted public health interventions. Furthermore, diagnosis and treatment centres must be capable of quickly diagnosing and treating infections regardless of HPM. Coverage of diagnosis and treatment centres should be broad, maintained in areas bordering malaria hotspots, and available to all febrile individuals

Human population movement and behavioural patterns in malaria hotspots on the Thai–Myanmar border: implications for malaria elimination

Abstract Background Malaria is heterogeneously distributed across landscapes. Human population movement (HPM) could link sub-regions with varying levels of transmission, leading to the persistence of disease even in very low transmission settings. Malaria along the Thai–Myanmar border has been decreasing, but remains heterogeneous. This study aimed to measure HPM, associated predictors of travel, and HPM correlates of self-reported malaria among people living within malaria hotspots. Methods 526 individuals from 279 households in two malaria hotspot areas were included in a prospective observational study. A baseline cross-sectional study was conducted at the beginning, recording both individual- and household-level characteristics. Individual movement and travel patterns were repeatedly observed over one dry season month (March) and one wet season month (May). Descriptive statistics, random effects logistic regressions, and logistic regressions were used to describe and determine associations between HPM patterns, individual-, household-factors, and self-reported malaria. Results Trips were more common in the dry season. Malaria risk was related to the number of days doing outdoor activities in the dry season, especially trips to Myanmar, to forest areas, and overnight trips. Trips to visit forest areas were more common among participants aged 20–39, males, individuals with low income, low education, and especially among individuals with forest-related occupations. Overnight trips were more common among males, and individual with forest-related occupations. Forty-five participants reported having confirmed malaria infection within the last year. The main place of malaria blood examination and treatment was malaria post and malaria clinic, with participants usually waiting for 2–3 days from onset fever to seeking diagnosis. Individuals using bed nets, living in houses with elevated floors, and houses that received indoor residual spraying in the last year were less likely to report malaria infection. Conclusion An understanding of HPM and concurrent malaria dynamics is important for consideration of targeted public health interventions. Furthermore, diagnosis and treatment centres must be capable of quickly diagnosing and treating infections regardless of HPM. Coverage of diagnosis and treatment centres should be broad, maintained in areas bordering malaria hotspots, and available to all febrile individuals

Community acceptability, participation, and adherence to mass drug administration with primaquine for Plasmodium vivax elimination in Southern Thailand: a mixed methods approach

Abstract Background Mass drug administration (MDA) with primaquine (PQ) is being considered for accelerating Plasmodium vivax elimination in remaining active foci. This study aimed to determine the acceptability of MDA with PQ in malaria endemic villages in a malarious setting in the South of Thailand undergoing MDA with PQ. Methods A cross-sectional mixed-methods approach was conducted in seven malaria endemic villages where MDA with PQ was implemented. The data were collected from community villagers and health workers using structured questionnaires, in-depth interviews, and focus group discussions. Descriptive statistics and logistic regression models were used for quantitative data analysis. Thematic analysis was applied for qualitative data. Results Among a total of 469 participants from the MDA villages, 293 participants were eligible for MDA with PQ and 79.86% (234) completed 14-days of PQ. The logistic regressions indicated that males (adjusted odds ratio: 2.52 [95% confidence interval: 1.33–4.81]) and those who are farmers (2.57 [1.12–5.90]) were most likely to participate in the MDA. Among 293 participants in the post-MDA study, 74.06% had originally agreed to participate in the MDA with PQ while 25.94% had originally reported not wanting to participate in the MDA. Of those who originally reported being willing to participate in the MDA, 71.23% followed through with participation in the first or second round. Conversely, 93.24% of those who originally reported not being willing to participate in the MDA did in fact participate in the MDA. Factors contributing to higher odds of agreeing to participate and following through with participation included being male (1.98 [1.06–3.69]) and correctly responding that malaria is preventable (2.32 [1.01–5.35]) with some differences by village. Five key themes emerged from the qualitative analyses: concern about side effects from taking PQ; disbelief that malaria could be eliminated in this setting; low overall concern about malaria infections; misunderstandings about malaria; and a general need to tailor public health efforts for this unique context. Conclusion While the reported likelihood of participating in MDA was high in this setting, actual follow-through was relatively moderate, partially because of eligibility (roughly 71% of those in the follow-up survey who originally agreed to participate actually followed through with participation). One of the largest concerns among study participants was PQ-related side effects—and these concerns likely heavily influenced participant adherence to the MDA. The results of this study can be used to tailor future MDAs, or other public health interventions, in this and potentially other similar settings

Spatial Heterogeneity and Temporal Trends in Malaria on the Thai–Myanmar Border (2012–2017): A Retrospective Observational Study

Malaria infections remain an important public health problem for the Thai–Myanmar border population, despite a plan for the elimination by the end of 2026 (Thailand) and 2030 (Myanmar). This study aimed to explore spatiotemporal patterns in Plasmodium falciparum and Plasmodium vivax incidence along the Thai–Myanmar border. Malaria cases among Thai citizens in 161 sub-districts in Thailand’s Kanchanaburi and Tak Provinces (2012–2017) were analyzed to assess the cluster areas and temporal trends. Based on reported incidence, 65.22% and 40.99% of the areas studied were seen to be at elimination levels for P. falciparum and P. vivax already, respectively. There were two clear clusters of malaria in the region: One in the northern part (Cluster I), and the other in the central part (Cluster II). In Cluster I, the malaria season exhibited two peaks, while there was only one peak seen for Cluster II. Malaria incidence decreased at a faster rate in Cluster I, with 5% and 4% reductions compared with 4% and 3% reductions in P. falciparum and P. vivax incidence per month, respectively, in Cluster II. The decreasing trends reflect the achievements of malaria control efforts on both sides of the Thai–Myanmar border. However, these clusters could act as reservoirs. Perhaps one of the main challenges facing elimination programs in this low transmission setting is maintaining a strong system for early diagnosis and treatment, even when malaria cases are very close to zero, whilst preventing re-importation of cases