Use of Google Earth to strengthen public health capacity and facilitate management of vector-borne diseases in resource-poor environments

GIS-Enhanced Survey of Potential Aedes aegypti and Aedes albopictus Artificial Oviposition Containers Distributed across Communities in Trinidad, West Indies

Dengue and other arboviruses remain a global threat, and enhanced efforts to control the mosquitoes that transmit them are urgently needed. A survey of potential manmade Aedes aegypti (L.) and Aedes albopictus (Skuse) oviposition containers was performed in four communities near the end of the typical dry season in 2018 in Trinidad, West Indies. The purpose was to conduct individual premise surveys and use GIS mapping to visualize premises within communities that had Aedes-positive containers, as this information could be used for the prioritization of mosquito control efforts in potential high risk areas as the wet season progressed. Accessible premises were surveyed following standard inspection protocols used by the Insect Vector Control Division (IVCD), Ministry of Health (MOH). The results indicated that two of the four locations would be at high risk for arbovirus transmission going into the wet season. The GIS mapping of premises with Aedes-positive containers facilitated the identification of potential hot spots for arbovirus transmission risk within communities that should be prioritized for enhanced monitoring and vector control efforts, emphasizing the need to increase community participation in standard surveys by IVCD.

Generating Contextual Variables From Web-Based Data for Health Research: Tutorial on Web Scraping, Text Mining, and Spatial Overlay Analysis

BACKGROUND

Contextual variables that capture the characteristics of delimited geographic or jurisdictional areas are vital for health and social research. However, obtaining data sets with contextual-level data can be challenging in the absence of monitoring systems or public census data.

OBJECTIVE

We describe and implement an 8-step method that combines web scraping, text mining, and spatial overlay analysis (WeTMS) to transform extensive text data from government websites into analyzable data sets containing contextual data for jurisdictional areas.

METHODS

This tutorial describes the method and provides resources for its application by health and social researchers. We used this method to create data sets of health assets aimed at enhancing older adults' social connections (eg, activities and resources such as walking groups and senior clubs) across the 374 health jurisdictions in Catalonia from 2015 to 2022. These assets are registered on a web-based government platform by local stakeholders from various health and nonhealth organizations as part of a national public health program. Steps 1 to 3 involved defining the variables of interest, identifying data sources, and using Python to extract information from 50,000 websites linked to the platform. Steps 4 to 6 comprised preprocessing the scraped text, defining new variables to classify health assets based on social connection constructs, analyzing word frequencies in titles and descriptions of the assets, creating topic-specific dictionaries, implementing a rule-based classifier in R, and verifying the results. Steps 7 and 8 integrate the spatial overlay analysis to determine the geographic location of each asset. We conducted a descriptive analysis of the data sets to report the characteristics of the assets identified and the patterns of asset registrations across areas.

RESULTS

We identified and extracted data from 17,305 websites describing health assets. The titles and descriptions of the activities and resources contained 12,560 and 7301 unique words, respectively. After applying our classifier and spatial analysis algorithm, we generated 2 data sets containing 9546 health assets (5022 activities and 4524 resources) with the potential to enhance social connections among older adults. Stakeholders from 318 health jurisdictions registered identified assets on the platform between July 2015 and December 2022. The agreement rate between the classification algorithm and verified data sets ranged from 62.02% to 99.47% across variables. Leisure and skill development activities were the most prevalent (1844/5022, 36.72%). Leisure and cultural associations, such as social clubs for older adults, were the most common resources (878/4524, 19.41%). Health asset registration varied across areas, ranging between 0 and 263 activities and 0 and 265 resources.

CONCLUSIONS

The sequential use of WeTMS offers a robust method for generating data sets containing contextual-level variables from internet text data. This study can guide health and social researchers in efficiently generating ready-to-analyze data sets containing contextual variables.

Spatial dispersal of <em>Aedes albopictus</em> mosquitoes captured by the modified sticky ovitrap in Selangor, Malaysia

Dengue is a major mosquito-borne disease in many tropical and sub-tropical countries worldwide, with entomological surveillance and control activities as the key management approaches. This study aimed to explore the spatial dispersal of the vector Aedes albopictus, captured by the modified sticky ovitrap (MSO) in residential areas with low-rise buildings in Selangor, Malaysia. Distribution maps were created and shown as temporally distinguished classes based on hotspot analysis by Getis-Ord; spatial autocorrelation assessed by semivariograms using the exponential Kernel function; and universal Kriging showing areas with estimated high and low vector densities. Distribution, hotspot and interpolated maps were analysed based on the total number of mosquitoes by month and week. All maps in the present study were generated and visualised in ArcMap. Spatial autocorrelation of Ae. albopictus based on the monthly occurrence of Ae. albopictus was found in March, April, October, November and December 2018, and when based on the weekly numbers, in weeks 1, 2, 3, 5, 7, 12, 14, 25, 26, 27, 31, 33, 42, 49 and 52. Semivariograms, based on the monthly and weekly numbers of Ae. albopictus, indicated spatial autocorrelation of the species extending between 50 and 70 m. The mosquito density maps reported in this study may provide beneficial information to facilitate implementation of more efficient entomological control activities.

The phylodynamics of emerging porcine deltacoronavirus (PDCoV) in Southeast Asia

Porcine deltacoronavirus (PDCoV), a recently emerging pathogen, causes diarrhea in pigs. A previous phylogenetic analysis based on spike genes suggested that PDCoV was divided into 3 different groups, including China, US, and Southeast Asia (SEA). SEA PDCoV, however, is genetically separated from China and US but shares a common ancestor. Its origin and evolution have yet been identified. Herein, phylodynamic analyses based on the full-length genome were performed to investigate the origin and evolution of SEA PDCoV. In the study, 18 full-length genome sequences of SEA PDCoV identified in 2013-2016 together with PDCoV from other regions were used in analyses. The results demonstrated that PDCoV was classified into 2 genogroups including G1 and G2. G1 is further evolved into G1a (China), G1b (US). G2 (SEA) group is further evolved into 3 clades, including SEA-1 (Thailand), SEA-2 (Vietnam), and SEA-2r (Vietnam recombinant) clades. The time to the most recent common ancestor (MRCA) of global PDCoV was estimated to be approximately 1989-1990 and possibly have been circulated in SEA more than a decade. SEA PDCoV is genetically diverse compared to China and US PDCoV. The substitution rate of SEA PDCoV was lower than those of China and US, but the recombination rate of SEA was higher. Recombination analyses revealed 4 potential recombinant events in SEA PDCoV, suggesting that they were derived from the same ancestor of China PDCoV. The SEA-2r subgroup was potentially recombinant between SEA-2 and US strains. In conclusion, major mechanisms driving the complex evolution and genetic diversity of SEA PDCoV were multiple introductions of exotic PDCoV strains followed by recombination. This article is protected by copyright. All rights reserved.

Urban mosquito management administration: Mosquito (Diptera: Culicidae) habitat surveillance and questionnaire survey in Wuhan, Central China

BACKGROUND

Creating National Sanitary City (CNSC) promotes appearance, environment sanitation and public health including vector management of cities in China. However, vector management especially mosquito management and the related administrative productivity of Patriotic Health Campaign System (PHCS) of National Sanitary Cities (NSCs) were questioned by many pest control professionals and citizens. In this study, we studied mosquito management of NSCs taking Wuhan as an example. The study aimed to (1) determine the distribution and abundance of immature mosquito habitats in built-up areas of Wuhan and (2) better understand the related administration procedure in CNSC.

METHODS

Immature mosquito habitat surveillance was carried out in randomly selected premises of driving schools (DSs), schools or kindergartens (SKs), property management residential areas (PMRAs), construction sites (CSs), wide roads with storm drains (WRSDs) and urban creeks (UCs) in built-up areas of Wuhan from July to October 2015 followed by questionnaire interviews with one each of premise occupants and district departments responsible for mosquito management in these premises.

RESULTS

Total of 64.1 km of route were inspected in 36 DSs, 36 SKs, 36 PMRAs, 36 CSs and 36 segments of WRSD and 2,158 potential mosquito habitats with 749 (35%) mosquito-positive habitats were found. The route index (RI) was 11.7, which was 14.6 times higher than the grade C criteria for vector density control (RI = 0.8 positive habitats/km) in CNSC. Occupants of 36 DSs, 36 SKs, 36 PMRAs, 34 CSs were interviewed and 77% of them reported no difference in mosquito infestation in their premises since 2013 and 80% of them knew about the responsibility and arrangements of PHCS of mosquito management in their premises. Only 15% had the awareness of larval source reduction strategy and 14% had implemented it. Receipt the electronic/paper edition of CNSC vector management specifications from the PHCS was very low (13%) and an official notification or bulletin for rectification mosquito-positive habitats was also very low (5%). Of the 75 responsible district departments interviewed, about half (55%) reported that they had held training courses/meetings related to CNSC vector management, the majority (96%) reported that they had not carried out independent on-site supervision of premises under their jurisdiction. No differences in larval indices were found between premises which were administrative intervened and with no administrative intervention.

CONCLUSIONS

The administrative intervention of PHCS had not evidently improved mosquito management of the premises in built-up areas in Wuhan. It is a violation of the original intention of the National Patriotic Health Campaign Committee in organizing CNSC programs. To combat mosquito borne diseases, and to improve the quality of life of residents, we recommend that PHCS honestly reveals defects in urban mosquito management and seriously takes those exposed defects. The PHCS should strengthen Patriotic Health Campaign activities by strict adherence to NSC standards. Further research on sustained promotion of urban mosquito management of NSCs, which focus on effective administration, as well as on improvement of related sectors of NSC standards should be carried out.

Online Advanced Analytical Service: Profiles for Dengue Hemorrhagic Fever Transmission in Southern Thailand

BACKGROUND

Southern Thailand has the highest Dengue Hemorrhagic Fever (DHF) incidence and fatality rate in Thailand. Geographic Information Systems (GIS) technology and spatial analysis techniques are powerful tools to describe epidemiological patterns. The aim of this study was to develop an Online Advanced Analytical Service: Profiles for Dengue Hemorrhagic Fever Transmission (OSD) in Southern Thailand.

METHODS

The system was developed using JavaServer Pages (JSP) and Database Management System (DBMS) with Structured Query Language (SQL) technology as the web database tool for data entry and data access, web Mathematica technology for data analysis and Google Maps™ API technology for online data display as the map service implementing GIS technology.

RESULTS

The OSD system has been available online at URL http://www.s-cm.co/dengue . Users performed data entry using the web-service with login by social network (i.e. Facebook) account, used data analysis tools with online real-time statistical analysis and data display with transparent color circles overlaid on Google Maps™.

CONCLUSION

The OSD system display represents the distribution of DHF cases with spatial information. This system enables health planners to provide interventions for DHF focusing on prevention, control, and strategic planning.

Use of mobile technology-based participatory mapping approaches to geolocate health facility attendees for disease surveillance in low resource settings

BACKGROUND

Identifying fine-scale spatial patterns of disease is essential for effective disease control and elimination programmes. In low resource areas without formal addresses, novel strategies are needed to locate residences of individuals attending health facilities in order to efficiently map disease patterns. We aimed to assess the use of Android tablet-based applications containing high resolution maps to geolocate individual residences, whilst comparing the functionality, usability and cost of three software packages designed to collect spatial information.

RESULTS

Using Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116 m (IQR 42-368) in Rizal and 493 m (IQR 258-886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks.

CONCLUSIONS

Results demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context.

Evolutionary and epidemiological analyses based on spike genes of porcine epidemic diarrhea virus circulating in Thailand in 2008-2015

Porcine epidemic diarrhea (PED) has been endemic causing sporadic outbreaks in Thailand since 2007. In 2014–2015, several herds had experienced severe PED outbreaks and the reason of the re-current outbreaks was unknown. Whether or not the introduction of exotic strains or continual evolution of existing PEDV, genetic analyses would provide a more understanding in its evolutionary pattern. In the study, 117 complete spike gene sequences of Thai PED virus (PEDV) collected from 2008 to 2015 were clustered along with 95 references of PEDV spike sequences, and analyzed with the US sequences dataset (n = 99).

The phylogenetic analysis demonstrated that Thai PEDV spike sequences were genetically diverse and had been influenced by multiple introduction of exotic strains. Although Thai PEDV have been evolved into 6 subgroups (TH1–6), Subgroup TH1 strains with the unique 9 nucleotides (CAA GGG AAT) insertion between 688th–689th position of spike (changing amino acid from N to TREY) insertion has become the dominant subgroup since 2014. Thai PEDV spike gene have higher evolutionary rate compare to that of the US sequences. One contributing factor would be the intra-recombination between subgroups. Thailand endemic strain should be assigned into new subclade of G2 (Thai pandemic variant).

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Thai isolates of PEDV developed their own clusters separated from other countries.

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There were multiple introductions of PEDV causing outbreaks in Thailand.

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Thai isolates have higher evolution than US isolates determined by the analysis in this study.

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There were 2 clades of PEDV, TH1 and TH2, which mainly causes the outbreaks in Thailand.

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There was a unique insertion of spike gene of Thai isolates between 2013-2015.

The Role of Spatial Statistics in the Control and Elimination of Neglected Tropical Diseases in Sub-Saharan Africa: A Focus on Human African Trypanosomiasis, Schistosomiasis and Lymphatic Filariasis

Disease control and elimination programmes can benefit greatly from accurate information on the spatial variability of disease risk, particularly when risk is highly spatially heterogeneous. Due to advances in statistical methodology, coupled with the increased availability of geospatial technology, this information is becoming increasingly accessible. In this chapter we describe recent advancements in spatial methods associated with the analysis of disease data measured at the point-level and demonstrate their application to the control and elimination of neglected tropical diseases (NTDs). We further provide information on spatially referenced data sources and software that can be used to create NTD risk maps, concentrating on those that can be freely obtained. Examples relating to three NTDs affecting populations in sub-Saharan Africa are presented throughout the chapter, i.e., human African trypanosomiasis, schistosomiasis and lymphatic filariasis. These three diseases, with differing routes of transmission, control methods and level of spatial heterogeneity, demonstrate the flexibility and applicability of the methods described.

Confidentiality considerations for use of social-spatial data on the social determinants of health: Sexual and reproductive health case study

Understanding whether and how the places where people live, work, and play are associated with health behaviors and health is essential to understanding the social determinants of health. However, social-spatial data which link a person and their attributes to a geographic location (e.g., home address) create potential confidentiality risks. Despite the growing body of literature describing approaches to protect individual confidentiality when utilizing social-spatial data, peer-reviewed manuscripts displaying identifiable individual point data or quasi-identifiers (attributes associated with the individual or disease that narrow identification) in maps persist, suggesting that knowledge has not been effectively translated into public health research practices. Using sexual and reproductive health as a case study, we explore the extent to which maps appearing in recent peer-reviewed publications risk participant confidentiality. Our scoping review of sexual and reproductive health literature published and indexed in PubMed between January 1, 2013 and September 1, 2015 identified 45 manuscripts displaying participant data in maps as points or small-population geographic units, spanning 26 journals and representing studies conducted in 20 countries. Notably, 56% (13/23) of publications presenting point data on maps either did not describe approaches used to mask data or masked data inadequately. Furthermore, 18% (4/22) of publications displaying data using small-population geographic units included at least two quasi-identifiers. These findings highlight the need for heightened education for researchers, reviewers, and editorial teams. We aim to provide readers with a primer on key confidentiality considerations when utilizing linked social-spatial data for visualizing results. Given the widespread availability of place-based data and the ease of creating maps, it is critically important to raise awareness on when social-spatial data constitute protected health information, best practices for masking geographic identifiers, and methods of balancing disclosure risk and scientific utility. We conclude with recommendations to support the preservation of confidentiality when disseminating results.

Development and evaluation of a spatial decision support system for malaria elimination in Bhutan

Background

Bhutan has reduced its malaria incidence significantly in the last 5 years, and is aiming for malaria elimination by 2016. To assist with the management of the Bhutanese malaria elimination programme a spatial decision support system (SDSS) was developed. The current study aims to describe SDSS development and evaluate SDSS utility and acceptability through informant interviews.

Methods

The SDSS was developed based on the open-source Quantum geographical information system (QGIS) and piloted to support the distribution of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) in the two sub-districts of Samdrup Jongkhar District. It was subsequently used to support reactive case detection (RACD) in the two sub-districts of Samdrup Jongkhar and two additional sub-districts in Sarpang District. Interviews were conducted to ascertain perceptions on utility and acceptability of 11 informants using the SDSS, including programme and district managers, and field workers.

Results

A total of 1502 households with a population of 7165 were enumerated in the four sub-districts, and a total of 3491 LLINs were distributed with one LLIN per 1.7 persons. A total of 279 households representing 728 residents were involved with RACD. Informants considered that the SDSS was an improvement on previous methods for organizing LLIN distribution, IRS and RACD, and could be easily integrated into routine malaria and other vector-borne disease surveillance systems. Informants identified some challenges at the programme and field level, including the need for more skilled personnel to manage the SDSS, and more training to improve the effectiveness of SDSS implementation and use of hardware.

Conclusions

The SDSS was well accepted and informants expected its use to be extended to other malaria reporting districts and other vector-borne diseases. Challenges associated with efficient SDSS use included adequate skills and knowledge, access to training and support, and availability of hardware including computers and global positioning system receivers.

Development and validation of a self-administered questionnaire to estimate the distance and mode of children's travel to school in urban India

Background

Although some 300 million Indian children travel to school every day, little is known about how they get there. This information is important for transport planners and public health authorities. This paper presents the development of a self-administered questionnaire and examines its reliability and validity in estimating distance and mode of travel to school in a low resource urban setting.

Methods

We developed a questionnaire on children’s travel to school. We assessed test re-test reliability by repeating the questionnaire one week later (n = 61). The questionnaire was improved and re-tested (n = 68). We examined the convergent validity of distance estimates by comparing estimates based on the nearest landmark to children’s homes with a ‘gold standard’ based on one-to-one interviews with children using detailed maps (n = 50).

Results

Most questions showed fair to almost perfect agreement. Questions on usual mode of travel (κ 0.73- 0.84) and road injury (κ 0.61- 0.72) were found to be more reliable than those on parental permissions (κ 0.18- 0.30), perception of safety (κ 0.00- 0.54), and physical activity (κ -0.01- 0.07). The distance estimated by the nearest landmark method was not significantly different than the in-depth method for walking , 52 m [95 % CI -32 m to 135 m], 10 % of the mean difference, and for walking and cycling combined, 65 m [95 % CI -30 m to 159 m], 11 % of the mean difference. For children who used motorized transport (excluding private school bus), the nearest landmark method under-estimated distance by an average of 325 metres [95 % CI −664 m to 1314 m], 15 % of the mean difference.

Conclusions

A self-administered questionnaire was found to provide reliable information on the usual mode of travel to school, and road injury, in a small sample of children in Hyderabad, India. The ‘nearest landmark’ method can be applied in similar low-resource settings, for a reasonably accurate estimate of the distance from a child’s home to school.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-015-0086-y) contains supplementary material, which is available to authorized users.

Integrating participatory community mobilization processes to improve dengue prevention: an eco-bio-social scaling up of local success in Machala, Ecuador

BACKGROUND

This project investigates the effectiveness and feasibility of scaling-up an eco-bio-social approach for implementing an integrated community-based approach for dengue prevention in comparison with existing insecticide-based and emerging biolarvicide-based programs in an endemic setting in Machala, Ecuador.

METHODS

An integrated intervention strategy (IIS) for dengue prevention (an elementary school-based dengue education program, and clean patio and safe container program) was implemented in 10 intervention clusters from November 2012 to November 2013 using a randomized controlled cluster trial design (20 clusters: 10 intervention, 10 control; 100 households per cluster with 1986 total households). Current existing dengue prevention programs served as the control treatment in comparison clusters. Pupa per person index (PPI) is used as the main outcome measure. Particular attention was paid to social mobilization and empowerment with IIS.

RESULTS

Overall, IIS was successful in reducing PPI levels in intervention communities versus control clusters, with intervention clusters in the six paired clusters that followed the study design experiencing a greater reduction of PPI compared to controls (2.2 OR, 95% CI: 1.2 to 4.7). Analysis of individual cases demonstrates that consideration for contexualizing programs and strategies to local neighborhoods can be very effective in reducing PPI for dengue transmission risk reduction.

CONCLUSIONS

In the rapidly evolving political climate for dengue control in Ecuador, integration of successful social mobilization and empowerment strategies with existing and emerging biolarvicide-based government dengue prevention and control programs is promising in reducing PPI and dengue transmission risk in southern coastal communities like Machala. However, more profound analysis of social determination of health is called for to assess sustainability prospects.

Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012)

BACKGROUND

Visual analytics aims to connect the processing power of information technologies and the user's ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution.

METHODS

We combined the complex joint spatio-temporal analysis with comprehensive visualisation. We analysed the spatio-temporal distribution of the campylobacteriosis in the Czech Republic between 2008 and 2012. We applied three main approaches in the study: (1) the geovisual analytics of the surveillance data that were visualised in the form of bubble chart; (2) the geovisual analytics of the disease's weekly incidence surfaces computed by spatio-temporal kriging and (3) the spatio-temporal scan statistics that was employed in order to identify high or low rates clusters of affected municipalities. The final data are stored in Keyhole Markup Language files and visualised in Google Earth™ in order to apply geovisual analytics.

RESULTS

Using geovisual analytics we were able to display and retrieve information from complex dataset efficiently. Instead of searching for patterns in a series of static maps or using numerical statistics, we created the set of interactive visualisations in order to explore and communicate results of analyses to the wider audience. The results of the geovisual analytics identified periodical patterns in the behaviour of the disease as well as fourteen spatio-temporal clusters of increased relative risk.

CONCLUSIONS

We prove that Google Earth™ software is a usable tool for the geovisual analysis of the disease distribution. Google Earth™ has many indisputable advantages (widespread, freely available, intuitive interface, space-time visualisation capabilities and animations, communication of results), nevertheless it is still needed to combine it with pre-processing tools that prepare the data into a form suitable for the geovisual analytics itself.

Spatio-temporal correlation networks of dengue in the state of Bahia

BACKGROUND

Dengue is a public health problem that presents complexity in its dissemination. The physical means of spreading and the dynamics of the spread between municipalities need to be analyzed to guide effective public policies to combat this problem.

METHODS

This study uses timing varying graph methods (TVG) to construct a correlation network between occurrences of reported cases of dengue between cities in the state of Bahia-Brazil. The topological network indices of all cities were correlated with dengue incidence using Spearman correlation. A randomization test was used to estimate the significance value of the correlation.

RESULTS

The correlation network presented a complex behavior with a heavy-tail distribution of the network edges weight. The randomization test exhibit a significant correlation (P < 0.0001) between the degree of each municipality in the network and the incidence of dengue in each municipality.

CONCLUSIONS

The hypothesis of the existence of a correlation between the occurrences of reported cases of dengue between different municipalities in the state of Bahia was validated. The significant correlation between the node degree and incidence, indicates that municipalities with high incidence are also responsible for the spread of the disease in the state. The method proposed suggests a new tool in epidemiological control strategy.

The social determinants of knowledge and perception on pulmonary tuberculosis among females in Jakarta, Indonesia

Background: Indonesia has not resolved tuberculosis burden since its prevalence and incidence has remained high. As the capital of Indonesia with a large population and a high number of tuberculosis cases, Jakarta has a distinctive condition of tuberculosis burden. This study aimed to obtain social determinants of knowledge and perception of pulmonary tuberculosis in an urban community.Methods: This study used 2,323 samples taken by random sampling in Jakarta during February-May 2011. Questionnaires were delivered to assess respondents’ knowledge and perception about pulmonary tuberculosis. Levels of knowledge were categorized into ‘poor’ and ‘good’. Perceptions about tuberculosis were measured by whether respondents perceived tuberculosis as a humiliating disease and a shunned disease.Results: Most respondents (88.7%) had good level of knowledge about tuberculosis, but misperception remained high (45.9%) in the community. Education level determined level of knowledge. The higher the education level the lower the risk of lack of knowledge. Tuberculosis perceptions were determined by family income and education level. Higher family income and education level were protective factors of misperception about tuberculosis as a humiliating disease and tendency to shun tuberculosis patients.Conclusion: People in urban area of Jakarta have good level of knowledge about tuberculosis, but it does not necessarily lead to proper perception of tuberculosis. Age, education level and having health insurance determined level of knowledge, while tuberculosis perceptions were determined much more by education level and family income. Tuberculosis control program should consider these determinants prior to developing a comprehensive strategy.

Mobile technologies and geographic information systems to improve health care systems: a literature review

Background

A growing body of research has employed mobile technologies and geographic information systems (GIS) for enhancing health care and health information systems, but there is yet a lack of studies of how these two types of systems are integrated together into the information infrastructure of an organization so as to provide a basis for data analysis and decision support. Integration of data and technical systems across the organization is necessary for efficient large-scale implementation.

Objective

The aim of this paper is to identify how mobile technologies and GIS applications have been used, independently as well as in combination, for improving health care.

Methods

The electronic databases PubMed, BioMed Central, Wiley Online Library, Scopus, Science Direct, and Web of Science were searched to retrieve English language articles published in international academic journals after 2005. Only articles addressing the use of mobile or GIS technologies and that met a prespecified keyword strategy were selected for review.

Results

A total of 271 articles were selected, among which 220 concerned mobile technologies and 51 GIS. Most articles concern developed countries (198/271, 73.1%), and in particular the United States (81/271, 29.9%), United Kingdom (31/271, 11.4%), and Canada (14/271, 5.2%). Applications of mobile technologies can be categorized by six themes: treatment and disease management, data collection and disease surveillance, health support systems, health promotion and disease prevention, communication between patients and health care providers or among providers, and medical education. GIS applications can be categorized by four themes: disease surveillance, health support systems, health promotion and disease prevention, and communication to or between health care providers. Mobile applications typically focus on using text messaging (short message service, SMS) for communication between patients and health care providers, most prominently reminders and advice to patients. These applications generally have modest benefits and may be appropriate for implementation. Integration of health data using GIS technology also exhibit modest benefits such as improved understanding of the interplay of psychological, social, environmental, area-level, and sociodemographic influences on physical activity. The studies evaluated showed promising results in helping patients treating different illnesses and managing their condition effectively. However, most studies use small sample sizes and short intervention periods, which means limited clinical or statistical significance.

Conclusions

A vast majority of the papers report positive results, including retention rate, benefits for patients, and economic gains for the health care provider. However, implementation issues are little discussed, which means the reasons for the scarcity of large-scale implementations, which might be expected given the overwhelmingly positive results, are yet unclear. There is also little combination between GIS and mobile technologies. In order for health care processes to be effective they must integrate different kinds of existing technologies and data. Further research and development is necessary to provide integration and better understand implementation issues.

The schisto track: a system for gathering and monitoring epidemiological surveys by connecting geographical information systems in real time

BACKGROUND

Using the Android platform as a notification instrument for diseases and disorders forms a new alternative for computerization of epidemiological studies.

OBJECTIVE

The objective of our study was to construct a tool for gathering epidemiological data on schistosomiasis using the Android platform.

METHODS

The developed application (app), named the Schisto Track, is a tool for data capture and analysis that was designed to meet the needs of a traditional epidemiological survey. An initial version of the app was finished and tested in both real situations and simulations for epidemiological surveys.

RESULTS

The app proved to be a tool capable of automation of activities, with data organization and standardization, easy data recovery (to enable interfacing with other systems), and totally modular architecture.

CONCLUSIONS

The proposed Schisto Track is in line with worldwide trends toward use of smartphones with the Android platform for modeling epidemiological scenarios.

Spatial distribution analysis of scrub typhus in Korea

OBJECTIVE

This study analyzes the spatial distribution of scrub typhus in Korea.

METHODS

A spatial distribution of Orientia tsutsugamushi occurrence using a geographic information system (GIS) is presented, and analyzed by means of spatial clustering and correlations.

RESULTS

The provinces of Gangwon-do and Gyeongsangbuk-do show a low incidence throughout the year. Some districts have almost identical environmental conditions of scrub typhus incidence. The land use change of districts does not directly affect the incidence rate.

CONCLUSION

GIS analysis shows the spatial characteristics of scrub typhus. This research can be used to construct a spatial-temporal model to understand the epidemic tsutsugamushi.

Cell phone-based system (Chaak) for surveillance of immatures of dengue virus mosquito vectors

Capture of surveillance data on mobile devices and rapid transfer of such data from these devices into an electronic database or data management and decision support systems promote timely data analyses and public health response during disease outbreaks. Mobile data capture is used increasingly for malaria surveillance and holds great promise for surveillance of other neglected tropical diseases. We focused on mosquito-borne dengue, with the primary aims of: 1) developing and field-testing a cell phone-based system (called Chaak) for capture of data relating to the surveillance of the mosquito immature stages, and 2) assessing, in the dengue endemic setting of Mérida, Mexico, the cost-effectiveness of this new technology versus paper-based data collection. Chaak includes a desktop component, where a manager selects premises to be surveyed for mosquito immatures, and a cell phone component, where the surveyor receives the assigned tasks and captures the data. Data collected on the cell phone can be transferred to a central database through different modes of transmission, including near-real time where data are transferred immediately (e.g., over the Internet) or by first storing data on the cell phone for future transmission. Spatial data are handled in a novel, semantically driven, geographic information system. Compared with a pen-and-paper-based method, use of Chaak improved the accuracy and increased the speed of data transcription into an electronic database. The cost-effectiveness of using the Chaak system will depend largely on the up-front cost of purchasing cell phones and the recurring cost of data transfer over a cellular network.

Spatiotemporal patterns of Aedes aegypti populations in Cairns, Australia: assessing drivers of dengue transmission

OBJECTIVES

To identify the meteorological drivers of dengue vector density and determine high- and low-risk transmission zones for dengue prevention and control in Cairns, Australia.

METHODS

Weekly adult female Ae. aegypti data were obtained from 79 double sticky ovitraps (SOs) located in Cairns for the period September 2007-May 2012. Maximum temperature, total rainfall and average relative humidity data were obtained from the Australian Bureau of Meteorology for the study period. Time series-distributed lag nonlinear models were used to assess the relationship between meteorological variables and vector density. Spatial autocorrelation was assessed via semivariography, and ordinary kriging was undertaken to predict vector density in Cairns.

RESULTS

Ae. aegypti density was associated with temperature and rainfall. However, these relationships differed between short (0-6 weeks) and long (0-30 weeks) lag periods. Semivariograms showed that vector distributions were spatially autocorrelated in September 2007-May 2008 and January 2009-May 2009, and vector density maps identified high transmission zones in the most populated parts of Cairns city, as well as Machans Beach.

CONCLUSION

Spatiotemporal patterns of Ae. aegypti in Cairns are complex, showing spatial autocorrelation and associations with temperature and rainfall. Sticky ovitraps should be placed no more than 1.2 km apart to ensure entomological coverage and efficient use of resources. Vector density maps provide evidence for the targeting of prevention and control activities. Further research is needed to explore the possibility of developing an early warning system of dengue based on meteorological and environmental factors.

Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti

Background

A remote sensing technique was developed which combines a Geographic Information System (GIS); Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner.

Methods

The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. The development and use of a remote sensing method was essential to the selection and location of random households.

Results

A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. 16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. A total of 55 households were located using this method during the 10 days of fieldwork in May and June of 2012.

Conclusions

The method used to generate and field locate random homes for surveys and water sampling was an effective means of selecting random households in a rural environment lacking geolocation infrastructure. The success rate for locating households using a handheld GPS was excellent and only rarely was local knowledge required to identify and locate households. This method provides an important technique that can be applied to other developing countries where a randomized study design is needed but infrastructure is lacking to implement more traditional participant selection methods.

Beyond information access: Support for complex cognitive activities in public health informatics tools

Public health professionals work with a variety of information sources to carry out their everyday activities. In recent years, interactive computational tools have become deeply embedded in such activities. Unlike the early days of computational tool use, the potential of tools nowadays is not limited to simply providing access to information; rather, they can act as powerful mediators of human-information discourse, enabling rich interaction with public health information. If public health informatics tools are designed and used properly, they can facilitate, enhance, and support the performance of complex cognitive activities that are essential to public health informatics, such as problem solving, forecasting, sense-making, and planning. However, the effective design and evaluation of public health informatics tools requires an understanding of the cognitive and perceptual issues pertaining to how humans work and think with information to perform such activities. This paper draws on research that has examined some of the relevant issues, including interaction design, complex cognition, and visual representations, to offer some human-centered design and evaluation considerations for public health informatics tools.

Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui

BACKGROUND

The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map.

METHODS

This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes.

RESULTS

Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script.

CONCLUSIONS

This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics data. Fourthly, we envisage an educational role for such applications.

Methods and tools for geographical mapping and analysis in primary health care

AIM

The purpose of this paper is to review methods and tools for mapping, visualising and exploring geographic information to aid in primary health care (PHC) research and development.

BACKGROUND

Mapping and spatial analysis of indicators of locality health profiles and healthcare needs assessment are well-established facets of health services research and development. However, while there are a range of different methods and tools used for these purposes, non-specialists responsible for managing the use of such information systems may find knowing where to start and what can be done a relatively steep learning curve. In this review, health and sociodemographic datasets are used to illustrate some key methods, tools and organisational issues, and builds upon two recent reviews in this journal, respectively, focusing on geographic data sources and geographic concepts. Those familiar with mapping and spatial analysis should find this a useful review of current matters.

METHOD

A thematic review is presented with illustrative case studies relevant to PHC. It begins with a section on visualising and interpreting geographic information. This is followed by a section critiquing analytical methods. Consideration is given to software and deployment issues in a third section. Content is based on domain knowledge of the authors as a team of geographic information scientists and a public health practitioner working in tandem, with its scope restricted to routine applications of mapping and analysis. Advanced techniques such as spatio-temporal modelling are not considered, neither are methodological technicalities, although guidance on further reading is provided.

SUMMARY

Geographical perspectives are now playing a significant role in PHC delivery, and for those engaged in informatics and/or managing population-level care, understanding key geographic information systems methods and terminologies are important as is gaining greater familiarity with institutional aspects of implementation.

Applying the global positioning system and google earth to evaluate the accessibility of birth services for pregnant women in northern Malawi

INTRODUCTION

The objective of this study was to validate the combined use of the Global Positioning System (GPS) and Google Earth for measuring the accessibility of health care facilities for pregnant women in northern Malawi.

METHODS

We used GPS and Google Earth to identify 5 major health care facilities in Mzuzu (Malawi) and the homes of 79 traditional birth attendants (TBAs). The distance and time required for each TBA to reach the nearest health care facility were measured by both GPS and by self-report of the TBAs. A convenience sample of 1138 pregnant women was interviewed about their choices of birth sites for current and previous pregnancies and the time and cost required to access health care facilities.

RESULTS

The correlation coefficient between the objective measurements by GPS and subjective reports by TBAs for time required from their homes to health care facilities was 0.654 (P < .001). Among pregnant women, 45.6% reported that they could reach a health care facility within 2 hours; 23.8% reported paying more than $1 for transportation to health care facilities. For the current study, 82.6% of women intended to give birth at a health care facility. However, only 48.7% of women actually gave birth in a health care facility in a previous pregnancy, and 32.6% were assisted by TBAs.

DISCUSSION

Combined GPS and Google Earth can be useful in the evaluation of accessibility of health care facilities, especially for emergency obstetric care.

Multi-disease data management system platform for vector-borne diseases

Background

Emerging information technologies present new opportunities to reduce the burden of malaria, dengue and other infectious diseases. For example, use of a data management system software package can help disease control programs to better manage and analyze their data, and thus enhances their ability to carry out continuous surveillance, monitor interventions and evaluate control program performance.

Methods and Findings

We describe a novel multi-disease data management system platform (hereinafter referred to as the system) with current capacity for dengue and malaria that supports data entry, storage and query. It also allows for production of maps and both standardized and customized reports. The system is comprised exclusively of software components that can be distributed without the user incurring licensing costs. It was designed to maximize the ability of the user to adapt the system to local conditions without involvement of software developers. Key points of system adaptability include 1) customizable functionality content by disease, 2) configurable roles and permissions, 3) customizable user interfaces and display labels and 4) configurable information trees including a geographical entity tree and a term tree. The system includes significant portions of functionality that is entirely or in large part re-used across diseases, which provides an economy of scope as new diseases downstream are added to the system at decreased cost.

Conclusions

We have developed a system with great potential for aiding disease control programs in their task to reduce the burden of dengue and malaria, including the implementation of integrated vector management programs. Next steps include evaluations of operational implementations of the current system with capacity for dengue and malaria, and the inclusion in the system platform of other important vector-borne diseases.

Emerging information technologies, such as data management system software packages, can help disease control programs to better manage and analyze their data, and thus make it easier to carry out continuous surveillance, monitor interventions and evaluate control program performance. This will lead to better informed decisions and actions. We have developed a multi-disease data management system platform with current capacity for dengue and malaria that supports data entry, storage and query. It also allows for production of maps and both standardized and customized reports. The system includes only software components that can be distributed without the user having to pay licensing costs. It was designed so that the user can adapt many aspects of the system to suit local conditions (for example roles and permissions, user interfaces and display labels and which functionality is included under a given disease) without having to involve software developers. In conclusion, we have developed a system capable of aiding disease control programs in their task to reduce the burden of dengue and malaria, including the implementation of integrated vector management programs. The next steps include operational implementations and evaluations of the current system with capacity for dengue and malaria, and the inclusion in the system platform of other important vector-borne diseases.

Free and simple GIS as appropriate for health mapping in a low resource setting: a case study in eastern Indonesia

BACKGROUND

Despite the demonstrated utility of GIS for health applications, there are perceived problems in low resource settings: GIS software can be expensive and complex; input data are often of low quality. This study aimed to test the appropriateness of new, inexpensive and simple GIS tools in poorly resourced areas of a developing country. GIS applications were trialled in pilot studies based on mapping of health resources and health indicators at the clinic and district level in the predominantly rural province of Nusa Tenggara Timur in eastern Indonesia. The pilot applications were (i) rapid field collection of health infrastructure data using a GPS enabled PDA, (ii) mapping health indicator data using open source GIS software, and (iii) service availability mapping using a free modelling tool.

RESULTS

Through contextualised training, district and clinic staff acquired skills in spatial analysis and visualisation and, six months after the pilot studies, they were using these skills for advocacy in the planning process, to inform the allocation of some health resources, and to evaluate some public health initiatives.

CONCLUSIONS

We demonstrated that GIS can be a useful and inexpensive tool for the decentralisation of health data analysis to low resource settings through the use of free and simple software, locally relevant training materials and by providing data collection tools to ensure data reliability.

Modern geographical reconnaissance of target populations in malaria elimination zones

Background

Geographical Reconnaissance (GR) operations using Personal Digital Assistants (PDAs) and Global Positioning Systems (GPS) have been conducted in the elimination provinces of Temotu, Solomon Islands and Tafea, Republic of Vanuatu. These operations aimed to examine modern approaches to GR to define the spatial distribution of target populations to support contemporary malaria elimination interventions.

Methods

Three GR surveys were carried out covering the outer islands of Temotu Province (October - November, 2008); Santa Cruz Island, Temotu Province (February 2009) and Tanna Island, Tafea Province (July - September 2009). Integrated PDA/GPS handheld units were used in the field to rapidly map and enumerate households, and collect associated population and household structure data to support priority elimination interventions, including bed net distribution, indoor residual spraying (IRS) and malaria case surveillance. Data were uploaded and analysed in customized Geographic Information System (GIS) databases to produce household distribution maps and generate relevant summary information pertaining to the GR operations. Following completion of field operations, group discussions were also conducted to review GR approaches and technology implemented.

Results

10,459 households were geo-referenced and mapped. A population of 43,497 and 30,663 household structures were recorded during the three GR surveys. The spatial distribution of the population was concentrated in coastal village clusters. Survey operations were completed over a combined total of 77 field days covering a total land mass area of approximately 1103.2 km². An average of 45 households, 118 structures and a population of 184 people were recorded per handheld device per day. Geo-spatial household distribution maps were also produced immediately following the completion of GR fieldwork. An overall high acceptability of modern GR techniques and technology was observed by both field operations staff and communities.

Conclusion

GR implemented using modern techniques has provided an effective and efficient operational tool for rapidly defining the spatial distribution of target populations in designated malaria elimination zones in Solomon Islands and Vanuatu. The data generated are being used for the strategic implementation and scaling-up of priority interventions, and will be essential for establishing future surveillance using spatial decision support systems.

Injury surveillance in low-resource settings using Geospatial and Social Web technologies

Background

Extensive public health gains have benefited high-income countries in recent decades, however, citizens of low and middle-income countries (LMIC) have largely not enjoyed the same advancements. This is in part due to the fact that public health data - the foundation for public health advances - are rarely collected in many LMIC. Injury data are particularly scarce in many low-resource settings, despite the huge associated burden of morbidity and mortality. Advances in freely-accessible and easy-to-use information and communication (ICT) technology may provide the impetus for increased public health data collection in settings with limited financial and personnel resources.

Methods and Results

A pilot study was conducted at a hospital in Cape Town, South Africa to assess the utility and feasibility of using free (non-licensed), and easy-to-use Social Web and GeoWeb tools for injury surveillance in low-resource settings. Data entry, geocoding, data exploration, and data visualization were successfully conducted using these technologies, including Google Spreadsheet, Mapalist, BatchGeocode, and Google Earth.

Conclusion

This study examined the potential for Social Web and GeoWeb technologies to contribute to public health data collection and analysis in low-resource settings through an injury surveillance pilot study conducted in Cape Town, South Africa. The success of this study illustrates the great potential for these technologies to be leveraged for public health surveillance in resource-constrained environments, given their ease-of-use and low-cost, and the sharing and collaboration capabilities they afford. The possibilities and potential limitations of these technologies are discussed in relation to the study, and to the field of public health in general.

Spatial risk assessments based on vector-borne disease epidemiologic data: importance of scale for West Nile virus disease in Colorado

We used epidemiologic data for human West Nile virus (WNV) disease in Colorado from 2003 and 2007 to determine 1) the degree to which estimates of vector-borne disease occurrence is influenced by spatial scale of data aggregation (county versus census tract), and 2) the extent of concordance between spatial risk patterns based on case counts versus incidence. Statistical analyses showed that county, compared with census tract, accounted for approximately 50% of the overall variance in WNV disease incidence, and approximately 33% for the subset of cases classified as West Nile neuroinvasive disease. These findings indicate that sub-county scale presentation provides valuable risk information for stakeholders. There was high concordance between spatial patterns of WNV disease incidence and case counts for census tract (83%) but not for county (50%) or zip code (31%). We discuss how these findings impact on practices to develop spatial epidemiologic data for vector-borne diseases and present data to stakeholders.

Use of technology to support information needs for continuity of operations planning in public health: a systematic review

OBJECTIVES

Continuity of operations planning focuses on an organization's ability to deliver essential services before, during and after an emergency. Public health leaders must make decisions based on information from many sources and their information needs are often facilitated or hindered by technology. The aim of this study is to provide a systematic review of studies of technology projects that address public health continuity of operations planning information needs and to discuss patterns, themes, and challenges to inform the design of public health continuity of operations information systems.

METHODS

To return a comprehensive results set in an under-explored area, we searched broadly in the Medline and EBSCOHost bibliographic databases using terms from prior work in public health emergency management and continuity of operations planning in other domains. In addition, we manually searched the citation lists of publications included for review.

RESULTS

A total of 320 publications were reviewed. Twenty studies were identified for inclusion (twelve risk assessment decision support tools, six network and communications-enabled decision support tools, one training tool and one dedicated video-conferencing tool). Levels of implementation for information systems in the included studies range from proposed frameworks to operational systems.

CONCLUSION

There is a general lack of documented efforts in the scientific literature for technology projects about public health continuity of operations planning. Available information about operational information systems suggest inclusion of public health practitioners in the design process as a factor in system success.

Developing global maps of the dominant anopheles vectors of human malaria

Simon Hay and colleagues describe how the Malaria Atlas Project has collated anopheline occurrence data to map the geographic distributions of the dominant mosquito vectors of human malaria.

ProactiveVector control strategies and improved monitoring and evaluation practices for dengue prevention

Despite tremendous efforts by public health organizations in dengue-endemic countries, it has proven difficult to achieve effective and sustainable control of the primary dengue virus vector Aedes aegypti (L.) and to effectively disrupt dengue outbreaks. This problem has multiple root causes, including uncontrolled urbanization, increased global spread of dengue viruses, and vector and dengue control programs not being provided adequate resources. In this forum article, we give an overview of the basic elements of a vector and dengue control program and describe a continuous improvement cyclical model to systematically and incrementally improve control program performance by regular efforts to identify ineffective methods and inferior technology, and then replacing them with better performing alternatives. The first step includes assessments of the overall resource allocation among vector/dengue control program activities, the efficacy of currently used vector control methods, and the appropriateness of technology used to support the program. We expect this will reveal that 1) some currently used vector control methods are not effective, 2) resource allocations often are skewed toward reactive vector control measures, and 3) proactive approaches commonly are underfunded and therefore poorly executed. Next steps are to conceptualize desired changes to vector control methods or technologies used and then to operationally determine in pilot studies whether these changes are likely to improve control program performance. This should be followed by a shift in resource allocation to replace ineffective methods and inferior technology with more effective and operationally tested alternatives. The cyclical and self-improving nature of the continuous improvement model will produce locally appropriate management strategies that continually are adapted to counter changes in vector population or dengue virus transmission dynamics. We discuss promising proactive vector control approaches and the continued need for the vector and dengue control community to incorporate emerging technologies and to partner with academia, business and the community-at-large to identify new solutions that reduce dengue.

Combining Google Earth and GIS mapping technologies in a dengue surveillance system for developing countries

Background

Dengue fever is a mosquito-borne illness that places significant burden on tropical developing countries with unplanned urbanization. A surveillance system using Google Earth and GIS mapping technologies was developed in Nicaragua as a management tool.

Methods and Results

Satellite imagery of the town of Bluefields, Nicaragua captured from Google Earth was used to create a base-map in ArcGIS 9. Indices of larval infestation, locations of tire dumps, cemeteries, large areas of standing water, etc. that may act as larval development sites, and locations of the homes of dengue cases collected during routine epidemiologic surveying were overlaid onto this map. Visual imagery of the location of dengue cases, larval infestation, and locations of potential larval development sites were used by dengue control specialists to prioritize specific neighborhoods for targeted control interventions.

Conclusion

This dengue surveillance program allows public health workers in resource-limited settings to accurately identify areas with high indices of mosquito infestation and interpret the spatial relationship of these areas with potential larval development sites such as garbage piles and large pools of standing water. As a result, it is possible to prioritize control strategies and to target interventions to highest risk areas in order to eliminate the likely origin of the mosquito vector. This program is well-suited for resource-limited settings since it utilizes readily available technologies that do not rely on Internet access for daily use and can easily be implemented in many developing countries for very little cost.

MIRO and IRbase: IT tools for the epidemiological monitoring of insecticide resistance in mosquito disease vectors

Background

Monitoring of insect vector populations with respect to their susceptibility to one or more insecticides is a crucial element of the strategies used for the control of arthropod-borne diseases. This management task can nowadays be achieved more efficiently when assisted by IT (Information Technology) tools, ranging from modern integrated databases to GIS (Geographic Information System). Here we describe an application ontology that we developed de novo, and a specially designed database that, based on this ontology, can be used for the purpose of controlling mosquitoes and, thus, the diseases that they transmit.

Methodology/Principal Findings

The ontology, named MIRO for Mosquito Insecticide Resistance Ontology, developed using the OBO-Edit software, describes all pertinent aspects of insecticide resistance, including specific methodology and mode of action. MIRO, then, forms the basis for the design and development of a dedicated database, IRbase, constructed using open source software, which can be used to retrieve data on mosquito populations in a temporally and spatially separate way, as well as to map the output using a Google Earth interface. The dependency of the database on the MIRO allows for a rational and efficient hierarchical search possibility.

Conclusions/Significance

The fact that the MIRO complies with the rules set forward by the OBO (Open Biomedical Ontologies) Foundry introduces cross-referencing with other biomedical ontologies and, thus, both MIRO and IRbase are suitable as parts of future comprehensive surveillance tools and decision support systems that will be used for the control of vector-borne diseases. MIRO is downloadable from and IRbase is accessible at VectorBase, the NIAID-sponsored open access database for arthropod vectors of disease.

It is a historical fact that a successful campaign against vector populations is one of the prerequisites for effectively fighting and eventually eradicating arthropod-borne diseases, be that in an epidemic or, even more so, in endemic cases. Based mostly on the use of insecticides and environmental management, vector control is now increasingly hampered by the occurrence of insecticide resistance that manifests itself, and spreads rapidly, briefly after the introduction of a (novel) chemical substance. We make use here of a specially built ontology, MIRO, to drive a new database, IRbase, dedicated to storing data on the occurrence of insecticide resistance in mosquito populations worldwide. The ontological approach to the design of databases offers the great advantage that these can be searched in an efficient way. Moreover, it also provides for an increased interoperability of present and future epidemiological tools. IRbase is now being populated by both older data from the literature and data recently collected from field.

Use of mapping and spatial and space-time modeling approaches in operational control of Aedes aegypti and dengue

The aims of this review paper are to 1) provide an overview of how mapping and spatial and space-time modeling approaches have been used to date to visualize and analyze mosquito vector and epidemiologic data for dengue; and 2) discuss the potential for these approaches to be included as routine activities in operational vector and dengue control programs. Geographical information system (GIS) software are becoming more user-friendly and now are complemented by free mapping software that provide access to satellite imagery and basic feature-making tools and have the capacity to generate static maps as well as dynamic time-series maps. Our challenge is now to move beyond the research arena by transferring mapping and GIS technologies and spatial statistical analysis techniques in user-friendly packages to operational vector and dengue control programs. This will enable control programs to, for example, generate risk maps for exposure to dengue virus, develop Priority Area Classifications for vector control, and explore socioeconomic associations with dengue risk.

A spatial national health facility database for public health sector planning in Kenya in 2008

BACKGROUND

Efforts to tackle the enormous burden of ill-health in low-income countries are hampered by weak health information infrastructures that do not support appropriate planning and resource allocation. For health information systems to function well, a reliable inventory of health service providers is critical. The spatial referencing of service providers to allow their representation in a geographic information system is vital if the full planning potential of such data is to be realized.

METHODS

A disparate series of contemporary lists of health service providers were used to update a public health facility database of Kenya last compiled in 2003. These new lists were derived primarily through the national distribution of antimalarial and antiretroviral commodities since 2006. A combination of methods, including global positioning systems, was used to map service providers. These spatially-referenced data were combined with high-resolution population maps to analyze disparity in geographic access to public health care.

FINDINGS

The updated 2008 database contained 5,334 public health facilities (67% ministry of health; 28% mission and nongovernmental organizations; 2% local authorities; and 3% employers and other ministries). This represented an overall increase of 1,862 facilities compared to 2003. Most of the additional facilities belonged to the ministry of health (79%) and the majority were dispensaries (91%). 93% of the health facilities were spatially referenced, 38% using global positioning systems compared to 21% in 2003. 89% of the population was within 5 km Euclidean distance to a public health facility in 2008 compared to 71% in 2003. Over 80% of the population outside 5 km of public health service providers was in the sparsely settled pastoralist areas of the country.

CONCLUSION

We have shown that, with concerted effort, a relatively complete inventory of mapped health services is possible with enormous potential for improving planning. Expansion in public health care in Kenya has resulted in significant increases in geographic access although several areas of the country need further improvements. This information is key to future planning and with this paper we have released the digital spatial database in the public domain to assist the Kenyan Government and its partners in the health sector.

Tracking the polio virus down the Congo River: a case study on the use of Google Earth in public health planning and mapping

BACKGROUND

The use of GIS in public health is growing, a consequence of a rapidly evolving technology and increasing accessibility to a wider audience. Google Earth (GE) is becoming an important mapping infrastructure for public health. However, generating traditional public health maps for GE is still beyond the reach of most public health professionals. In this paper, we explain, through the example of polio eradication activities in the Democratic Republic of Congo, how we used GE Earth as a planning tool and we share the methods used to generate public health maps.

RESULTS

The use of GE improved field operations and resulted in better dispatch of vaccination teams and allocation of resources. It also allowed the creation of maps of high quality for advocacy, training and to help understand the spatiotemporal relationship between all the entities involved in the polio outbreak and response.

CONCLUSION

GE has the potential of making mapping available to a new set of public health users in developing countries. High quality and free satellite imagery, rich features including Keyhole Markup Language or image overlay provide a flexible but yet powerful platform that set it apart from traditional GIS tools and this power is still to be fully harnessed by public health professionals.