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This paper explores the possibility of integrating knowledge mapping into a conceptual framework that could serve as a tool for understanding the many complex processes, resources and people involved in a health system, and for identifying potential gaps within knowledge translation processes in order to address them. After defining knowledge mapping, this paper presents various examples of the application of this process in health, before looking at the steps that need to be taken to identify potential gaps, to determine to what extent these gaps affect the knowledge translation process and to establish their cause. This is followed by proposals for interventions aimed at strengthening the overall process. Finally, potential limitations on the application of this framework at the country level are addressed.

Abstract Background Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network. Results This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.×, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage. Conclusion By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

Abstract Objective A great deal of international attention has been focussed recently on how much additional funding is required to scale up health interventions to meet global targets such as the Millennium Development Goals (MDGs). Most of the cost estimates that have been made in response have assumed that unit costs of delivering services will not change as coverage increases or as more and more interventions are delivered together. This is most unlikely. The main objective of this paper is to measure the impact of patient load on the cost per visit at primary health care facilities and the extent to which this would influence estimates of the costs and financial requirements to scale up interventions. Methods Multivariate regression analysis was used to explore the determinants of variability in unit costs using data for 44 countries with a total of 984 observations. Findings Controlling for other possible determinants, we find that the cost of an outpatient visit is very sensitive to the number of patients seen by providers each day at primary care facilities. Each 1% increase in patient through-put results, on average, in a 27% reduction in the cost per visit (p < 0.0001), which can lead to a difference of up to $30 in the observed costs of an outpatient visit at primary facilities in the same setting, other factors held constant. Conclusion Variability in capacity utilization, therefore, need to be taken into account in cost estimates, and the paper develops a method by which this can be done.

Abstract Background Reducing the potential for large scale loss of life, large numbers of casualties, and widespread displacement of populations that can result from natural disasters is a difficult challenge for the individuals, communities and governments that need to respond to such events. While it is extremely difficult, if not impossible, to predict the occurrence of most natural hazards; it is possible to take action before emergency events happen to plan for their occurrence when possible and to mitigate their potential effects. In this context, an Atlas of Disaster Risk is under development for the 21 Member States that constitute the World Health Organization's (WHO) Eastern Mediterranean (EM) Region and the West Bank and Gaza Strip territory. Methods and Results This paper describes the Geographic Information System (GIS) based methods that have been used in order to create the first volume of the Atlas which looks at the spatial distribution of 5 natural hazards (flood, landslide, wind speed, heat and seismic hazard). It also presents the results obtained through the application of these methods on a set of countries part of the EM Region before illustrating how this type of information can be aggregated for decision making. Discussion and Conclusion The methods presented in this paper aim at providing a new set of tools for GIS practitioners to refine their analytical capabilities when examining natural hazards, and at the same time allowing users to create more specific and meaningful local analyses. The maps resulting from the application of these methods provides decision makers with information to strengthen their disaster management capacity. It also represents the basis for the reflection that needs to take place regarding populations' vulnerability towards natural hazards from a health perspective.

Abstract Background Sub-national figures providing information about the wealth of the population are useful in defining the spatial distribution of both economic activity and poverty within any given country. Furthermore, since several health indicators such as life expectancy are highly correlated with household welfare, sub-national figures allow for the estimation of the distribution of these health indicators within countries when direct measurement is difficult. We have developed methods that utilize spatially distributed information, including night-time light imagery and population to model the distribution of income per capita, as a proxy for wealth, at the country and sub-national level to support the estimation of the distribution of correlated health indicators. Results A first set of analysis are performed in order to propose a new global model for the prediction of income per capita at the country level. A second set of analysis is then confirming the possibility to transfer the country level approach to the sub-national level on a country by country basis before underlining the difficulties to create a global or regional models for the extrapolation of sub-national figures when no country data set exists. Conclusions The methods described provide promising results for the extrapolation of national and sub-national income per capita figures. These results are then discussed in order to evaluate if the proposed methods could not represent an alternative approach for the generation of consistent country specific and/or global poverty maps disaggregated to some sub-national level.

Dengue is a major public health problem in Myanmar. The country aims to reduce morbidity by 50% and mortality by 90% by 2025 based on 2015 data. To support efforts to reach these goals it is important to have a detailed picture of the epidemiology of dengue, its relationship to meteorological factors and ideally to predict ahead of time numbers of cases to plan resource allocations and control efforts. Health facility-level data on numbers of dengue cases from 2012 to 2017 were obtained from the Vector Borne Disease Control Unit, Department of Public Health, Myanmar. A detailed analysis of routine dengue and dengue hemorrhagic fever (DHF) incidence was conducted to examine the spatial and temporal epidemiology. Incidence was compared to climate data over the same period. Dengue was found to be widespread across the country with an increase in spatial extent over time. The temporal pattern of dengue cases and fatalities was episodic with annual outbreaks and no clear longitudinal trend. There were 127,912 reported cases and 632 deaths from 2012 and 2017 with peaks in 2013, 2015 and 2017. The case fatality rate was around 0.5% throughout. The peak season of dengue cases was from May to August in the wet season but in 2014 peak dengue season continued until November. The strength of correlation of dengue incidence with different climate factors (total rainfall, maximum, mean and minimum temperature and absolute humidity) varied between different States and Regions. Monthly incidence was forecasted 1 month ahead using the Auto Regressive Integrated Moving Average (ARIMA) method at country and subnational levels. With further development and validation, this may be a simple way to quickly generate short-term predictions at subnational scales with sufficient certainty to use for intervention planning., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Zaw et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

After publication of our article [1], we have been notified that an extra alpha symbol (α) was mistakenly added at the beginning of the title.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic fatal lung disease without a cure and new drug strategies are urgently needed. Differences in behavior between diseased and healthy cells are well known and drug response can be different between cells isolated from IPF patients and controls. The macrolide Azithromycin (AZT) has anti-inflammatory and immunomodulatory properties. Recently anti-fibrotic effects have been described. However, the anti-fibrotic effects on primary IPF-fibroblasts (FB) directly compared to control-FB are unknown. We hypothesized that IPF-FB react differently to AZT in terms of anti-fibrotic effects., Methods: Primary normal human lung and IPF-FB were exposed to TGF-β (5 ng/ml), Azithromycin (50 μM) alone or in combination prior to gene expression analysis. Pro-collagen Iα1 secretion was assessed by ELISA and protein expression by western blot (αSMA, Fibronectin, ATP6V1B2, LC3 AB (II/I), p62, Bcl-xL). Microarray analysis was performed to screen involved genes and pathways after Azithromycin treatment in control-FB. Apoptosis and intraluminal lysosomal pH were analyzed by flow cytometry., Results: AZT significantly reduced collagen secretion in TGF-β treated IPF-FB compared to TGF-β treatment alone, but not in control-FB. Pro-fibrotic gene expression was similarly reduced after AZT treatment in IPF and control-FB. P62 and LC3II/I western blot revealed impaired autophagic flux after AZT in both control and IPF-FB with significant increase of LC3II/I after AZT in control and IPF-FB, indicating enhanced autophagy inhibition. Early apoptosis was significantly higher in TGF-β treated IPF-FB compared to controls after AZT. Microarray analysis of control-FB treated with AZT revealed impaired lysosomal pathways. The ATPase and lysosomal pH regulator ATP6V0D2 was significantly less increased after additional AZT in IPF-FB compared to controls. Lysosomal function was impaired in both IPF and control FB, but pH was significantly more increased in TGF-β treated IPF-FB., Conclusion: We report different treatment responses after AZT with enhanced anti-fibrotic and pro-apoptotic effects in IPF compared to control-FB. Possibly impaired lysosomal function contributes towards these effects. In summary, different baseline cell phenotype and behavior of IPF and control cells contribute to enhanced anti-fibrotic and pro-apoptotic effects in IPF-FB after AZT treatment and strengthen its role as a new potential anti-fibrotic compound, that should further be evaluated in clinical studies.

Emergency obstetric and newborn care (EmONC) can be life-saving in managing well-known complications during childbirth. However, suboptimal availability, accessibility, quality and utilisation of EmONC services hampered meeting Millennium Development Goal target 5A. Evaluation and modelling tools of health system performance and future potential can help countries to optimise their strategies towards reaching Sustainable Development Goal (SDG) 3: ensure healthy lives and promote well-being for all at all ages. The standard set of indicators for monitoring EmONC has been found useful for assessing quality and utilisation but does not account for travel time required to physically access health services. The increased use of geographical information systems, availability of free geographical modelling tools such as AccessMod and the quality of geographical data provide opportunities to complement the existing EmONC indicators by adding geographically explicit measurements. This paper proposes three additional EmONC indicators to the standard set for monitoring EmONC; two consider physical accessibility and a third addresses referral time from basic to comprehensive EmONC services. We provide examples to illustrate how the AccessMod tool can be used to measure these indicators, analyse service utilisation and propose options for the scaling-up of EmONC services. The additional indicators and analysis methods can supplement traditional EmONC assessments by informing approaches to improve timely access to achieve Universal Health Coverage and reach SDG 3., Competing Interests: Competing interests: None declared.

Bleomycin-induced lung injury leads to surfactant dysfunction and permanent loss of alveoli due to a remodeling process called collapse induration. Collapse induration also occurs in acute interstitial lung disease and idiopathic pulmonary fibrosis in humans. We hypothesized that surfactant dysfunction aggravates lung injury and early remodeling resulting in collapse induration within 7 days after lung injury. Rats received bleomycin to induce lung injury and either repetitive surfactant replacement therapy (SRT: 100 mg Curosurf/kg BW = surf group) or saline (0.9% NaCl = saline group). After 3 (D3) or 7 (D7) days, invasive pulmonary function tests were performed to determine tissue elastance (H) and static compliance (Cst). Bronchoalveolar lavage (BAL) was taken for surfactant function, inflammatory markers, and protein measurements. Lungs were fixed by vascular perfusion for design-based stereology and electron microscopic analyses. SRT significantly improved minimum surface tension of alveolar surfactant as well as H and Cst at D3 and D7. At D3 decreased inflammatory markers including neutrophilic granulocytes, IL-1β, and IL-6 correlated with reduced BAL-protein levels after SRT. Numbers of open alveoli were significantly increased at D3 and D7 in SRT groups whereas at D7 there was also a significant reduction in septal wall thickness and parenchymal tissue volume. Septal wall thickness and numbers of open alveoli highly correlated with improved lung mechanics after SRT. In conclusion, reduction in surface tension was effective to stabilize alveoli linked with an attenuation of parameters of acute lung injury at D3 and collapse induration at D7. Hence, SRT modifies disease progression to collapse induration., (Copyright © 2017 the American Physiological Society.)

Lysophosphatidic acid (LPA) signaling through one of its receptors, LPA1, contributes to both the development and the pathological remodeling after injury of many organs. Because we found previously that LPA-LPA1 signaling contributes to pulmonary fibrosis, here we investigated whether this pathway is also involved in lung development. Quantitative assessment of lung architecture of LPA1-deficient knock-out (KO) and wild-type (WT) mice at 3, 12, and 24 weeks of age using design-based stereology suggested the presence of an alveolarization defect in LPA1 KO mice at 3 weeks, which persisted as alveolar numbers increased in WT mice into adulthood. Across the ages examined, the lungs of LPA1 KO mice exhibited decreased alveolar numbers, septal tissue volumes, and surface areas, and increased volumes of the distal airspaces. Elastic fibers, critical to the development of alveolar septa, appeared less organized and condensed and more discontinuous in KO alveoli starting at P4. Tropoelastin messenger RNA expression was decreased in KO lungs, whereas expression of matrix metalloproteinases degrading elastic fibers was either decreased or unchanged. These results are consistent with the abnormal lung phenotype of LPA1 KO mice, being attributable to reduced alveolar septal formation during development, rather than to increased septal destruction as occurs in the emphysema of chronic obstructive pulmonary disease. Peripheral septal fibroblasts and myofibroblasts, which direct septation in late alveolarization, demonstrated reduced production of tropoelastin and matrix metalloproteinases, and diminished LPA-induced migration, when isolated from LPA1 KO mice. Taken together, our data suggest that LPA-LPA1 signaling is critically required for septation during alveolarization.

Background and Objective: Rhinoviruses (RV) replicate in both upper and lower airway epithelial cells. We evaluated the possibility of using nasal epithelial cells (NEC) as surrogate of bronchial epithelial cells (BEC) for RV pathogenesis cell culture studies., Methods: We used primary paired NEC and BEC cultures established from healthy subjects and compared the replication of RV belonging to the major (RV16) and minor (RV1B) group, and the cellular antiviral and proinflammatory cytokine responses towards these viruses. We related antiviral and pro-inflammatory responses of NEC isolated from CF and COPD patients with those of BEC., Results: RV16 replication and major group surface receptor (ICAM-1) expression were higher in healthy NEC compared with BEC (P < 0.05); RV1B replication and minor group surface receptor (LDLR) expression were similar. Healthy NEC and BEC produced similar levels of IFN-β and IFN-λ2/3 upon RV infection or after simulation with poly(IC). IL-8 production was similar between healthy NEC and BEC. IL-6 release at baseline (P < 0.01) and upon infection with RV16 (P < 0.05) and poly(IC) stimulation (P < 0.05) was higher in NEC. RV1B viral load in NEC was related to RV1B viral load in BEC (r = 0.49, P = 0.01). There was a good correlation of IFN levels between NEC and BEC (r = 0.66, P = 0.0004 after RV1B infection). IL-8 production in NEC was related to IL-8 production in BEC (r = 0.48, P = 0.02 after RV1B infection)., Conclusion: NEC are a suitable alternative cellular system to BEC to study the pathophysiology of RV infections and particularly to investigate IFN responses induced by RV infection., (© 2015 Asian Pacific Society of Respirology.)

As the deadline for the millennium development goals approaches, it has become clear that the goals linked to maternal and newborn health are the least likely to be achieved by 2015. It is therefore critical to ensure that all possible data, tools and methods are fully exploited to help address this gap. Among the methods that are under-used, mapping has always represented a powerful way to 'tell the story' of a health problem in an easily understood way. In addition to this, the advanced analytical methods and models now being embedded into Geographic Information Systems allow a more in-depth analysis of the causes behind adverse maternal and newborn health (MNH) outcomes. This paper examines the current state of the art in mapping the geography of MNH as a starting point to unleashing the potential of these under-used approaches. Using a rapid literature review and the description of the work currently in progress, this paper allows the identification of methods in use and describes a framework for methodological approaches to inform improved decision-making. The paper is aimed at health metrics and geography of health specialists, the MNH community, as well as policy-makers in developing countries and international donor agencies.

This article discusses options to allow comparative analysis of inequalities in the distribution of health workers (HWs) across and within countries using a single summary measure of the distribution. Income inequality generally is measured across individuals, but inequalities in the dispersion of HWs must use geographical areas or population groupings as units of analysis. The article first shows how this change of observational unit creates a resolution problem for various inequality indices and then tests how sensitive a simple ratio measure of the distribution of HWs is to changes in resolution. This ratio of inequality is illustrated first with the global distribution of HWs and then with its distributions within Indonesia. The resolution problem is not solved through this new approach, and indicators of inequalities of access to HWs or health services more generally appear not to be comparable across countries. Investigating geographical inequalities over time in one setting is possible but only if the units of analysis remain the same over time.

Background: Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network., Results: This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.x, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage., Conclusion: By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

Objective: A great deal of international attention has been focussed recently on how much additional funding is required to scale up health interventions to meet global targets such as the Millennium Development Goals (MDGs). Most of the cost estimates that have been made in response have assumed that unit costs of delivering services will not change as coverage increases or as more and more interventions are delivered together. This is most unlikely. The main objective of this paper is to measure the impact of patient load on the cost per visit at primary health care facilities and the extent to which this would influence estimates of the costs and financial requirements to scale up interventions., Methods: Multivariate regression analysis was used to explore the determinants of variability in unit costs using data for 44 countries with a total of 984 observations., Findings: Controlling for other possible determinants, we find that the cost of an outpatient visit is very sensitive to the number of patients seen by providers each day at primary care facilities. Each 1% increase in patient through-put results, on average, in a 27% reduction in the cost per visit (p < 0.0001), which can lead to a difference of up to $30 in the observed costs of an outpatient visit at primary facilities in the same setting, other factors held constant., Conclusion: Variability in capacity utilization, therefore, need to be taken into account in cost estimates, and the paper develops a method by which this can be done.

Background: Reducing the potential for large scale loss of life, large numbers of casualties, and widespread displacement of populations that can result from natural disasters is a difficult challenge for the individuals, communities and governments that need to respond to such events. While it is extremely difficult, if not impossible, to predict the occurrence of most natural hazards; it is possible to take action before emergency events happen to plan for their occurrence when possible and to mitigate their potential effects. In this context, an Atlas of Disaster Risk is under development for the 21 Member States that constitute the World Health Organization's (WHO) Eastern Mediterranean (EM) Region and the West Bank and Gaza Strip territory., Methods and Results: This paper describes the Geographic Information System (GIS) based methods that have been used in order to create the first volume of the Atlas which looks at the spatial distribution of 5 natural hazards (flood, landslide, wind speed, heat and seismic hazard). It also presents the results obtained through the application of these methods on a set of countries part of the EM Region before illustrating how this type of information can be aggregated for decision making., Discussion and Conclusion: The methods presented in this paper aim at providing a new set of tools for GIS practitioners to refine their analytical capabilities when examining natural hazards, and at the same time allowing users to create more specific and meaningful local analyses. The maps resulting from the application of these methods provides decision makers with information to strengthen their disaster management capacity. It also represents the basis for the reflection that needs to take place regarding populations' vulnerability towards natural hazards from a health perspective.

BACKGROUND: Sub-national figures providing information about the wealth of the population are useful in defining the spatial distribution of both economic activity and poverty within any given country. Furthermore, since several health indicators such as life expectancy are highly correlated with household welfare, sub-national figures allow for the estimation of the distribution of these health indicators within countries when direct measurement is difficult.We have developed methods that utilize spatially distributed information, including night-time light imagery and population to model the distribution of income per capita, as a proxy for wealth, at the country and sub-national level to support the estimation of the distribution of correlated health indicators. RESULTS: A first set of analysis are performed in order to propose a new global model for the prediction of income per capita at the country level. A second set of analysis is then confirming the possibility to transfer the country level approach to the sub-national level on a country by country basis before underlining the difficulties to create a global or regional models for the extrapolation of sub-national figures when no country data set exists. CONCLUSIONS: The methods described provide promising results for the extrapolation of national and sub-national income per capita figures. These results are then discussed in order to evaluate if the proposed methods could not represent an alternative approach for the generation of consistent country specific and/or global poverty maps disaggregated to some sub-national level.