Absence Of Local Data Research Articles

Interpolation of Precipitation Extremes on a Large Domain Toward IDF Curve Construction at Unmonitored Locations

An intensity–duration–frequency (IDF) curve describes the relationship between rainfall intensity and duration for a given return period and location. Such curves are obtained through frequency analysis of rainfall data and commonly used in infrastructure design, flood protection, water management, and urban drainage systems. However, they are typically available only in sparse locations. Data for other sites must be interpolated as the need arises. This paper describes how extreme precipitation of several durations can be interpolated to compute IDF curves on a large, sparse domain. In the absence of local data, a reconstruction of the historical meteorology is used as a covariate for interpolating extreme precipitation characteristics. This covariate is included in a hierarchical Bayesian spatial model for extreme precipitations. This model is especially well suited for a covariate gridded structure, thereby enabling fast and precise computations. As an illustration, the methodology is used to construct IDF curves over Eastern Canada. An extensive cross-validation study shows that at locations where data are available, the proposed method generally improves on the current practice of Environment and Climate Change Canada which relies on a moment-based fit of the Gumbel extreme-value distribution.

Effective coastal adaptation needs accurate hazard assessment: a case study in Port Resolution, Tanna Island Vanuatu

Developing countries face risks from coastal hazards that are being amplified by climate change. The selection of effective adaptation interventions to manage these risks requires a sufficiently accurate assessment of the coastal hazard at a given location. Yet challenges remain in terms of understanding local coastal risks given the coarseness of global wave models and the paucity of locally scaled data in most developing countries, including Small Island Developing States (SIDS) like Vanuatu. This paper aims to examine the differences in hazard assessment and adaptation option selections arising from analyses using globally versus locally scaled data on coastal processes. As a case study, we focused on an eroding cliff face in Port Resolution on Tanna Island, Vanuatu, which is of concern to the local community and government authorities. The coastal process modeling revealed that the global wave data generated unrealistically high predictions of wave height within Port Resolution Bay. Expensive engineering adaptations designed to provide coastal protection were therefore likely to fail in preventing ongoing cliff erosion. In this case, the best adaptation solution involves changing land use to revegetate and help stabilize the cliff top. Our case study highlights the importance of accurate hazard assessment, especially in data-poor regions where the extrapolation of global datasets and models in the absence of local data can result in poor adaptation decision-making. Furthermore, the multidisciplinary approach applied here can be applied in other data-poor regions to strengthen analyses exploring the benefits of local adaptation interventions.

Economic and disease burden of Japanese encephalitis in Zhejiang Province, 2013-2018.

BackgroundJapanese encephalitis (JE) is a mosquito-borne disease and associated with high mortality and disability rate among symptomatic cases. In the absence of local data, this study estimated the economic burden and the disability-adjusted life years (DALYs) due to JE in Zhejiang Province, China during 2013–2018, to increase disease awareness and provide evidence for effective health policy.Methodology/Principle findingsWe merged multiple data sources, including National Notifiable Disease Registry System (NNDRS), patient interviews and medical records from corresponding hospitals for JE cases which occurred during 2013–2018 in Zhejiang Province. Direct costs were extracted from hospitals’ billing systems and patient interviews. Indirect costs and disease burden were calculated based on questionnaire survey from patient interviews and follow-up assessment by general practitioners. Given under-reporting, an expansion factor (EF) was applied to extrapolate the JE burden to the provincial level. The total economic burden of JE during 2013–2018 was estimated at US $12.01 million with an EF = 3. Of this, $8.32 million was due to direct economic cost and $3.69 million to indirect cost. The disease burden of JE was 42.75 DALYs per million population (28.44 YLD, 14.28 YLL) according to the 1990 Global Burden of Disease (GBD 1990) methodology and 80.01 DALYs (53.67YLD, 26.34YLL) according to the GBD 2010 methodology. Sensitivity analysis demonstrated that the overall economic burden varied from US$ 1.73–36.42 million. The greatest variation was due to the prognosis of illness (-85.57%-203.17%), followed by occupation (-34.07%-134.12%) and age (-72.97%-47.69%).Conclusions/SignificanceJE imposes a heavy burden for families and society in Zhejiang Province. This study provides comprehensive empirical estimates of JE burden to increase awareness and strengthen knowledge of the public. These data may support provincial level public health decision making for prevention and control of JE. Ongoing surveillance for acute meningitis and encephalitis syndrome (AEMS) in sentinel hospitals, is needed to further refine estimates of JE burden.

Survey of Work Zone Practices and Validation of Highway Capacity Manual Work Zone Capacity Model

Capacity at work zones is one of the major factors affecting queueing at work zones. Different states within the United States use their own methodology in determining work zone capacities and when to implement lane closures at work zones. The objective of this study was two-fold: first, to provide a synthesis of work zone lane closure procedures practiced by the various Departments of Transportation (DOTs) nationwide; and secondly, to validate the Highway Capacity Manual 6th edition’s (HCM 6) work zone capacity model using field-collected data in the state of Louisiana. The first objective was met by administering a survey to DOTs nationwide. The survey revealed that half of the states that responded to the survey require minimum capacity for short-term work zone lane closures, with minimum capacity ranging from 1100 to 1900 passenger cars per hour per lane. In addition, most of the states reported implementing consistent policies across various district offices. The survey findings provide a good source of information on queue analysis and work zone lane closure policies adopted across different DOTs. The second objective was met by collecting traffic flow data from 10 work zone sites within the state of Louisiana and validating the capacity model in the HCM 6. Results showed the HCM 6 model slightly overestimating the average field-observed capacity by 6%. In the absence of local data, the HCM 6 model provides a great tool to estimate work zone capacities in Louisiana.

COVID-19 length of hospital stay: a systematic review and data synthesis

BackgroundThe COVID-19 pandemic has placed an unprecedented strain on health systems, with rapidly increasing demand for healthcare in hospitals and intensive care units (ICUs) worldwide. As the pandemic escalates, determining the resulting needs for healthcare resources (beds, staff, equipment) has become a key priority for many countries. Projecting future demand requires estimates of how long patients with COVID-19 need different levels of hospital care.MethodsWe performed a systematic review of early evidence on length of stay (LoS) of patients with COVID-19 in hospital and in ICU. We subsequently developed a method to generate LoS distributions which combines summary statistics reported in multiple studies, accounting for differences in sample sizes. Applying this approach, we provide distributions for total hospital and ICU LoS from studies in China and elsewhere, for use by the community.ResultsWe identified 52 studies, the majority from China (46/52). Median hospital LoS ranged from 4 to 53 days within China, and 4 to 21 days outside of China, across 45 studies. ICU LoS was reported by eight studies—four each within and outside China—with median values ranging from 6 to 12 and 4 to 19 days, respectively. Our summary distributions have a median hospital LoS of 14 (IQR 10–19) days for China, compared with 5 (IQR 3–9) days outside of China. For ICU, the summary distributions are more similar (median (IQR) of 8 (5–13) days for China and 7 (4–11) days outside of China). There was a visible difference by discharge status, with patients who were discharged alive having longer LoS than those who died during their admission, but no trend associated with study date.ConclusionPatients with COVID-19 in China appeared to remain in hospital for longer than elsewhere. This may be explained by differences in criteria for admission and discharge between countries, and different timing within the pandemic. In the absence of local data, the combined summary LoS distributions provided here can be used to model bed demands for contingency planning and then updated, with the novel method presented here, as more studies with aggregated statistics emerge outside China.

Rethinking collaboration: developing a learning platform to address under-five mortality in Mpumalanga province, South Africa.

Following 50 years of apartheid, South Africa introduced visionary health policy committing to the right to health as part of a primary health care (PHC) approach. Implementation is seriously challenged, however, in an often-dysfunctional health system with scarce resources and a complex burden of avoidable mortality persists. Our aim was to develop a process generating evidence of practical relevance on implementation processes among people excluded from access to health systems. Informed by health policy and systems research, we developed a collaborative learning platform in which we worked as co-researchers with health authorities in a rural province. This article reports on the process and insights brought by health systems stakeholders. Evidence gaps on under-five mortality were identified with a provincial Directorate after which we collected quantitative and qualitative data. We applied verbal autopsy to quantify levels, causes and circumstances of deaths and participatory action research to gain community perspectives on the problem and priorities for action. We then re-convened health systems stakeholders to analyse and interpret these data through which several systems issues were identified as contributory to under-five deaths: staff availability and performance; service organization and infrastructure; multiple parallel initiatives; and capacity to address social determinants. Recommendations were developed ranging from immediate low- and no-cost re-organization of services to those where responses from higher levels of the system or outside were required. The process was viewed as acceptable and relevant for an overburdened system operating ‘in the dark’ in the absence of local data. Institutional infrastructure for evidence-based decision-making does not exist in many health systems. We developed a process connecting research evidence on rural health priorities with the means for action and enabled new partnerships between communities, authorities and researchers. Further development is planned to understand potential in deliberative processes for rural PHC.

A new database of on-road vehicle emission factors for Colombia: A case study of Bogotá

Mobile sources contribute directly or indirectly with most of the atmospheric emissions in Colombian cities. Quantification of mobile source emissions rely on emission factors (EF) and vehicle activity. However, EF for vehicles in the country have not evolved at the same time as fleet renovation and fuel composition changes in the last few years. In fact, estimated EF before 2010 may not reflect the reduction of sulfur content in diesel and the renovation and deterioration of passenger vehicles; therefore, emission levels may be over or under estimated. To account for these changes, we have implemented the MOVES model in Bogota and obtained a new database of on-road vehicle emission factors. For this purpose, local information of activity rates, speed profiles, vehicle population distribution and age, meteorology and fuel composition was used. Emissions were estimated with these new set of EF and compared with previous inventories. We observed large reductions in SO2 (-87%), CO (-65%) and VOC (-62%) emissions from mobiles sources and lower reductions in NOx (-20%). Other pollutants such as PM2.5 (+15%) and CO2 (+28%) reported increases. This paper includes a new database of on-road vehicle emission factors for Bogota, which can be applied in other Colombian cities in the absence of local data.

Plasma glucose in screening for diabetes and pre-diabetes: how much is too much? Analysis of fasting plasma glucose and oral glucose tolerance test in Sri Lankans

BackgroundFasting plasma glucose (FPG) is the most commonly used screening tool for diabetes in Sri Lanka. Cut-off values from American Diabetes Association recommendations are adopted in the absence of local data. We aimed to establish FPG cut offs for Sri Lankans to screen for diabetes and pre-diabetes.MethodsData on FPG and diabetes/pre-diabetes status were obtained from Sri Lanka Diabetes and Cardiovascular Study (SLDCS), a community based island wide observational study conducted in 2005–6. Sensitivity specificity and area under the ROC curve were calculated for different FPG values.ResultsStudy included 4014 community dwelling people after excluding people already on treatment for diabetes or pre-diabetes. Mean age was 45.3 (± 15) years and 60.4% were females. FPG cut off of 5.3 mmol/L showed better sensitivity and specificity than 5.6 mmol/L in detecting diabetes (87.8% and 84.4% Vs 80.8% and 92.1%) and pre-diabetes (54.7% and 87.0% Vs 43.8% and 94.2%).ConclusionsA lower FPG cut off of 5.3 mmol/L has a better sensitivity and acceptable specificity in screening for diabetes and pre-diabetes in Sri Lankan adults.

Economic burden of dengue in Indonesia.

BackgroundDengue is associated with significant economic expenditure and it is estimated that the Asia Pacific region accounts for >50% of the global cost. Indonesia has one of the world’s highest dengue burdens; Aedes aegypti and Aedes albopictus are the primary and secondary vectors. In the absence of local data on disease cost, this study estimated the annual economic burden during 2015 of both hospitalized and ambulatory dengue cases in Indonesia.MethodsTotal 2015 dengue costs were calculated using both prospective and retrospective methods using data from public and private hospitals and health centres in three provinces: Yogyakarta, Bali and Jakarta. Direct costs were extracted from billing systems and claims; a patient survey captured indirect and out-of-pocket costs at discharge and 2 weeks later. Adjustments across sites based on similar clinical practices and healthcare landscapes were performed to fill gaps in cost estimates. The national burden of dengue was extrapolated from provincial data using data from the three sites and applying an empirically-derived epidemiological expansion factor.ResultsTotal direct and indirect costs per dengue case assessed at Yogyakarta, Bali and Jakarta were US$791, US$1,241 and US$1,250, respectively. Total 2015 economic burden of dengue in Indonesia was estimated at US$381.15 million which comprised US$355.2 million for hospitalized and US$26.2 million for ambulatory care cases.ConclusionDengue imposes a substantial economic burden for Indonesian public payers and society. Complemented with an appropriate weighting method and by accounting for local specificities and practices, these data may support national level public health decision making for prevention/control of dengue in public health priority lists.

High rate of non-susceptibility to metronidazole and clindamycin in anaerobic isolates: Data from a clinical laboratory from Karachi, Pakistan

Due to increasing resistance amongst anaerobic pathogens periodic surveillance of resistance has been recommended in regional/local settings. Anaerobic antimicrobial susceptibility testing is not routinely performed in many laboratories in Pakistan, hence absence of local data may lead to inappropriate empirical therapy in serious cases. 121 clinically significant anaerobic strains (26/121; 21% bacteremic isolates) were isolated and saved from 2010 to 2011. Susceptibility testing against metronidazole, clindamycin, co-amoxiclav, meropenem, piperacillin/tazobactam, linezolid and gatifloxacin was performed by determining minimum inhibitory concentrations (MICs). A high proportion of non-susceptible strains to metronidazole (10% of 121 isolates) and clindamycin (12% of 121 isolates) was seen, most noticeable in Bacteroides fragilis. Three Bacteroides species strains were non-susceptible to both metronidazole and clindamycin. One strain of Clostridium species was fully resistant to metronidazole and had intermediate resistance to clindamycin. No resistance to any of the other tested antibiotics was seen. Resistance to metronidazole was higher in bacteremic vs. non bacteremic isolates (p = value 0.07). In our setting where there is a high usage of empirical metronidazole and clindamycin for the treatment of serious anaerobic infections clinicians should be aware of increased resistance to these agents. Periodic surveillance of resistance to anti-anaerobic drugs especially metronidazole and clindamycin should be performed to generate antibiogram and guide appropriate empiric therapy.

Constraining ecosystem carbon dynamics in a data-limited world: integrating ecological "common sense" in a model–data fusion framework

Abstract. Many of the key processes represented in global terrestrial carbon models remain largely unconstrained. For instance, plant allocation patterns and residence times of carbon pools are poorly known globally, except perhaps at a few intensively studied sites. As a consequence of data scarcity, carbon models tend to be underdetermined, and so can produce similar net fluxes with very different parameters and internal dynamics. To address these problems, we propose a series of ecological and dynamic constraints (EDCs) on model parameters and initial conditions, as a means to constrain ecosystem variable inter-dependencies in the absence of local data. The EDCs consist of a range of conditions on (a) carbon pool turnover and allocation ratios, (b) steady-state proximity, and (c) growth and decay of model carbon pools. We use a simple ecosystem carbon model in a model–data fusion framework to determine the added value of these constraints in a data-poor context. Based only on leaf area index (LAI) time series and soil carbon data, we estimate net ecosystem exchange (NEE) for (a) 40 synthetic experiments and (b) three AmeriFlux tower sites. For the synthetic experiments, we show that EDCs lead to an overall 34% relative error reduction in model parameters, and a 65% reduction in the 3 yr NEE 90% confidence range. In the application at AmeriFlux sites all NEE estimates were made independently of NEE measurements. Compared to these observations, EDCs resulted in a 69–93% reduction in 3 yr cumulative NEE median biases (–0.26 to +0.08 kg C m−2), in comparison to standard 3 yr median NEE biases (–1.17 to −0.84 kg C m−2). In light of these findings, we advocate the use of EDCs in future model–data fusion analyses of the terrestrial carbon cycle.

Implementing agricultural phosphorus science and management to combat eutrophication.

Experience with implementing agricultural phosphorus (P) strategies highlights successes and uncertainty over outcomes. We examine case studies from the USA, UK, and Sweden under a gradient of voluntary, litigated, and regulatory settings. In the USA, voluntary strategies are complicated by competing objectives between soil conservation and dissolved P mitigation. In litigated watersheds, mandated manure export has not wrought dire consequences on poultry farms, but has adversely affected beef producers who fertilize pastures with manure. In the UK, regulatory and voluntary approaches are improving farmer awareness, but require a comprehensive consideration of P management options to achieve downstream reductions. In Sweden, widespread subsidies sometime hinder serious assessment of program effectiveness. In all cases, absence of local data can undermine recommendations from models and outside experts. Effective action requires iterative application of existing knowledge of P fate and transport, coupled with unabashed description and demonstration of tradeoffs to local stakeholders.

Economic Impact of Reduced Mortality Due to Increased Cycling

Increasing regular physical activity is a key public health goal. One strategy is to change the physical environment to encourage walking and cycling, requiring partnerships with the transport and urban planning sectors. Economic evaluation is an important factor in the decision to fund any new transport scheme, but techniques for assessing the economic value of the health benefits of cycling and walking have tended to be less sophisticated than the approaches used for assessing other benefits. This study aimed to produce a practical tool for estimating the economic impact of reduced mortality due to increased cycling. The tool was intended to be transparent, easy to use, reliable, and based on conservative assumptions and default values, which can be used in the absence of local data. It addressed the question: For a given volume of cycling within a defined population, what is the economic value of the health benefits?The authors used published estimates of relative risk of all-cause mortality among regular cyclists and applied these to levels of cycling defined by the user to produce an estimate of the number of deaths potentially averted because of regular cycling. The tool then calculates the economic value of the deaths averted using the “value of a statistical life.” The outputs of the tool support decision making on cycle infrastructure or policies, or can be used as part of an integrated economic appraisal. The tool's unique contribution is that it takes a public health approach to a transport problem, addresses it in epidemiologic terms, and places the results back into the transport context. Examples of its use include its adoption by the English and Swedish departments of transport as the recommended methodologic approach for estimating the health impact of walking and cycling.

Establishment of generic transformations for geotechnical design parameters

Geotechnical design parameters are typically estimated based on the transformations from site investigation results. In general, one expects the transformation uncertainty to change depending on the number and type of sites in the database. This study tries to address the following two issues pertaining to the transformation uncertainty: (a) how transformation uncertainties change with the number and type of sites in the database and (b) whether transformation uncertainties will eventually fall within a narrow range when a “generic” transformation is developed from a sufficiently large database. This study also attempts to propose a framework to establish such a generic transformation and quantify its uncertainty. This framework is demonstrated by the transformation between piezocone CPTU data and undrained shear strengths (Su) of clays. It was found that the CPTU–Su transformation and its uncertainty is site or region-dependent, and the “local” transformation equation from one site may not be applicable to another site, both in terms of the mean trend (which is well known) as well as the coefficient of variation (c.o.v.). An approach is proposed to develop the generic CPTU–Su transformation equations that can be applied for downstream reliability analysis or design in the absence of local data. Sensitivity analysis shows that it requires data from at least 15 sites with the accompanying implicit assumption that sufficient geographical coverage typically implies sufficient geologic diversity to reliably build such “generic” transformation equations.

Sociodemographic and geographic variability in smoking in the U.S.: A multilevel analysis of the 2006–2007 Current Population Survey, Tobacco Use Supplement

Because smoking is a pervasive risk factor for numerous health outcomes, it is essential to understand smoking patterns in different populations and places. Previous studies have described sociodemographic and geographic variation in smoking across the U.S., providing insight to public health scientists aiming to identify high-risk populations and places in the absence of local data. This study extends previous research by considering the influence of a combination of covariates at the U.S. state, core-based statistical area (CBSA), and individual levels, focusing on a time period when smoking prevalence has decreased significantly but disparities remain. We applied multilevel regression to the 2006–2007 Current Population Survey–Tobacco Use Supplement. We conducted a four-level logistic regression model and evaluated fixed and random effects to quantify the contribution of sociodemographic characteristics at the individual level, area poverty at the CBSA level, and indoor smoking legislation and cigarette taxes at the state level, to the probability of smoking at the individual level and the variance in smoking at the state and CBSA levels. Sociodemographic covariates were significant predictors of smoking and explained 67% of variance at the CBSA level alone but only 41% at the state level. Contextual covariates alone, such as indoor smoking legislation and cigarette taxes at the state level and area poverty at the CBSA level, explained a larger proportion of state variance (82%) but individually had modest statistical significance. Our findings emphasize the continued disparities in smoking patterns in the U.S. despite the decrease of smoking prevalence in the past decade; as well as the ongoing necessity to consider associations with both compositional and contextual factors. Patterns of residual variance emphasize the continued need to identify and evaluate appropriate contextual covariates, with more refined geographic resolution than that available from national surveys at present.

Seismic-zonation of Port-au-Prince Using Pixel- and Object-based Imaging Analysis Methods on ASTER GDEM

We report about a preliminary study to evaluate the use of semi-automated imaging analysis of remotely-sensed DEM and field geophysical measurements to develop a seismic-zonation map of Port-au-Prince, Haiti. For in situ data, V .30 values are derived from the MASW technique deployed in and around the city. For satellite imagery, we use an ASTER GDEM of Hispaniola. We apply both pixel- and object-based imaging methods on the ASTER GDEM to explore local topography (absolute elevation values) and classify terrain types such as mountains, alluvial fans and basins/near-shore regions. We assign NEHRP seismic site class ranges based on available V .30 values. A comparison of results from imagery-based methods to results from traditional geologic-based approaches reveals good overall correspondence. We conclude that image analysis of RS data provides reliable first-order site characterization results in the absence of local data and can be useful to refine detailed site maps with sparse local data.

Default Values for Highway Capacity and Level-of-Service Analyses

The Highway Capacity Manual (HCM) is the authoritative source providing state-of-the-art methodologies for evaluating highway, transit, bicycle, and pedestrian facilities. Default values are used to represent input parameters when the input parameters are difficult to measure or estimate. A default value is a representative value that may be appropriate for estimating an input parameter in the absence of local data. Before this study was done, no nationwide research effort had been conducted to assemble field measurements to determine whether the default values in the HCM represent typical field conditions. A sensitivity analysis was conducted for the input parameters in HCM 2000 that influence the service measures calculated in the HCM methodologies. Nineteen of these input parameters were determined to have a high degree of sensitivity in influencing the service measure results. These sensitive input parameters influence the service measures for the following HCM chapters: Urban Streets, Signalized Intersections, Pedestrians, Bicycle Paths, Multilane Highways, and Basic Freeway Segments. Based on the assembly of a nationwide database, specific default values were recommended for heavy vehicle percentages and peak-hour factors for uninterrupted flow facilities (freeways, multilane highways, and rural two-lane highways). It is recommended that default values for some input parameters continue to be developed based on existing HCM guidance. Other input parameters should be based on field measurements obtained from design plans. Additional guidance is provided to aid in the selection of default values based on the review of recent research documents.

Distribution différentielle des Odonates et des Salmonidés indigènes et exogènes dans la réserve d’Orlu (Ariège, France)

Differential distribution of Odonates and indigenous and exogenous salmonids in Orlu Protected Area (Ariège, France). — Species introduction may constitute an important threat to indigenous biodiversity. The naturalization of Brook Trout Salvelinus fontinalis in the Orlu Protected Area (Ariège, France) may affect local communities, especially Odonates. We surveyed the wetlands of this protected area in order to compare the distributions of Odonates and salmonids. Our results showed that the Brook Trout was absent in nearly all reproduction sites of Odonates. Brown Trout Salmo trutta fario was present in some of these sites. The sites where salmonids were present generally hosted few or no Odonates. Other sites were characterized by a relatively important typological and odonatological diversity, with specific assemblages that often showed an ecological and/or a heritage value. The spatial segregation was more conspicuous between Brook Trout and Odonates than between these latter and Brown Trout. Then, an eventual impact of Brook Trout on Odonates is plausible, but remains unconfirmed in our study in the absence of local data on the microhabitats occupied by both taxa.