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Background In 2005, Bangladesh, India and Nepal agreed to eliminate visceral leishmaniasis (VL) as a public health problem. The approach to this was through improved case detection and treatment, and controlling transmission by the sand fly vector Phlebotomus argentipes, with indoor residual spraying (IRS) of insecticide. Initially, India applied DDT with stirrup pumps for IRS, however, this did not reduce transmission. After 2015 onwards, the pyrethroid alpha-cypermethrin was applied with compression pumps, and entomological surveillance was initiated in 2016. Methods Eight sentinel sites were established in the Indian states of Bihar, Jharkhand and West Bengal. IRS coverage was monitored by household survey, quality of insecticide application was measured by HPLC, presence and abundance of the VL vector was monitored by CDC light traps, insecticide resistance was measured with WHO diagnostic assays and case incidence was determined from the VL case register KAMIS. Results Complete treatment of houses with IRS increased across all sites from 57% in 2016 to 70% of houses in 2019, rising to >80% if partial house IRS coverage is included (except West Bengal). The quality of insecticide application has improved compared to previous studies, average doses of insecticide on filters papers ranged from 1.52 times the target dose of 25mg/m2 alpha-cypermethrin in 2019 to 1.67 times in 2018. Resistance to DDT has continued to increase, but the vector was not resistant to carbamates, organophosphates or pyrethroids. The annual and seasonal abundance of P. argentipes declined between 2016 to 2019 with an overall infection rate of 0.03%. This was associated with a decline in VL incidence for the blocks represented by the sentinel sites from 1.16 per 10,000 population in 2016 to 0.51 per 10,000 in 2019. Conclusion Through effective case detection and management reducing the infection reservoirs for P. argentipes in the human population combined with IRS keeping P. argentipes abundance and infectivity low has reduced VL transmission. This combination of effective case management and vector control has now brought India within reach of the VL elimination targets., Author summary Visceral Leishmaniasis (VL), also known as kala-azar, is a major parasitic disease in South Asia (Indian subcontinent), with 85% of the disease incidence in India. Historically VL had been controlled and almost eliminated with Indoor Residual Spraying (IRS) using dichlorodiphenyltrichloroethane (DDT). However, reinitiating this approach in 2015 failed due to high insecticide resistance in the sand fly vector and poor IRS quality, meaning that VL elimination targets were not met. To improve this the National Vector Borne Disease Control Programme changed to an effective insecticide, alpha-cypermethrin and altered the mode of application to compression pumps. Sentinel sites were established to monitor the entomological indicators, these showed the positive impact of these changes from 2016 to 2019. During this period the overall incidence of disease has decreased, and India is now on track to reach it’s target incidence for VL of less than 1/1000 people at the sub-district (block) level.

To better prevent the potential risks in Internet-based Supply Chain Financing (SCF) products, this paper optimizes and evaluates the Internet-based SCF-oriented Credit Risk Evaluation (CRE) method. Firstly, this paper summarizes 12 risk factors of SCF business, establishes a Risk Assessment Index System (RAIS) with good consistency and stability; then, the principles of Backpropagation (BP) Neural Network (NN) is expounded together with Support Vector Machines (SVM) and Genetic Algorithm (GA) model. Consequently, a CRE model is implemented by the NN tools in MATLAB based on the collection of multiple groups of SCF-oriented risk assessment samples. Subsequently, the assessment samples are trained and tested. Finally, the SCF-oriented CRE model is proposed and verified. The results show that the BP-GA model has presented high prediction consistency with the actual classification. According to the comparison of classification results of SVM, BP model, and BP-GA model, the classification accuracy of test samples of the proposed Internet-based SCF-oriented CRE system using BP-GA model reaches 97.19%; the Type I and Type II error rate of the CRE system based on BP-GA model is 7.2% and 14.21%, respectively. Therefore, a suitable SCF-oriented CRE method is put forward for China’s commercial banks along with scientific and feasible suggestions to manage SCF-oriented credit risks more reasonably and effectively.

Background Ward-Based Outreach Teams’ (WBOTs) use of mobile technologies can promote better quality and improved health services for populations in low- and middle-income countries. However, the implementation of such systems is fraught with threats to sustainability. Purpose The purpose of this study was to gain a deeper understanding of users’ views and experiences of the implementation of mHealth in a selected sub-district in North West Province, South Africa. Methods The study was qualitative, exploratory and descriptive. Data were collected from community health workers (CHWs) (n = 24) and outreach team leaders (OTLs) (n = 4) who used mobile devices loaded with the Mobenzi application through semi-structured focus group interviews, using an interview guide. Creswell’s stages of thematic analysis were used for data analysis, and codes, categories and themes were validated with the participants. Results Three themes emerged from the findings, namely the transition from a paper-based system to an electronic system; the use of the application; and reverting to paper-based documentation. The findings revealed that WBOTs considered the mHealth application as useful, easy to use, and supportive to their workflow. They experienced some technical challenges and lamented the inaccessibility of technicians. The mobile initiative’s termination caused distress among the participants, especially CHWs who had to revert to paper-based documentation to capture community health data. OTLs were concerned about the quality of health data being captured in the absence of the application. Conclusions The study concluded that community-based health care programmes that use WBOTs and mHealth technologies are essential in strengthening the health care system. WBOTs are facilitators for improving access to health care. Policy-makers and district managers will gain useful insights if they engage application users in discussions regarding future mobile health interventions for household and community-based care.

Background Work to control the gambiense form of human African trypanosomiasis (gHAT), or sleeping sickness, is now directed towards ending transmission of the parasite by 2030. In order to supplement gHAT case-finding and treatment, since 2011 tsetse control has been implemented using Tiny Targets in a number of gHAT foci. As this intervention is extended to new foci, it is vital to understand the costs involved. Costs have already been analysed for the foci of Arua in Uganda and Mandoul in Chad. This paper examines the costs of controlling Glossina palpalis palpalis in the focus of Bonon in Côte d’Ivoire from 2016 to 2017. Methodology/Principal findings Some 2000 targets were placed throughout the main gHAT transmission area of 130 km2 at a density of 14.9 per km2. The average annual cost was USD 0.5 per person protected, USD 31.6 per target deployed of which 12% was the cost of the target itself, or USD 471.2 per km2 protected. Broken down by activity, 54% was for deployment and maintenance of targets, 34% for tsetse surveys/monitoring and 12% for sensitising populations. Conclusions/Significance The cost of tsetse control per km2 of the gHAT focus protected in Bonon was more expensive than in Chad or Uganda, while the cost per km2 treated, that is the area where the targets were actually deployed, was cheaper. Per person protected, the Bonon cost fell between the two, with Uganda cheaper and Chad more expensive. In Bonon, targets were deployed throughout the protected area, because G. p. palpalis was present everywhere, whereas in Chad and Uganda G. fuscipes fuscipes was found only the riverine fringing vegetation. Thus, differences between gHAT foci, in terms of tsetse ecology and human geography, impact on the cost-effectiveness of tsetse control. It also demonstrates the need to take into account both the area treated and protected alongside other impact indicators, such as the cost per person protected., Author summary Sleeping sickness is a fatal disease in Africa caused by trypanosomes transmitted by the bite of infected tsetse flies. The World Health Organization has set the absence of new infections as a goal for 2030. To achieve this, screening and treatment of patients is supplemented by tsetse control. Tiny Targets are small insecticide-impregnated panels of blue cloth and black netting which attract and kill tsetse. To maintain the momentum in these last stages of eliminating the disease, it is important to understand the costs of vector control. This paper presents the results of two years’ cost monitoring in Bonon, an area covering 130 km2, home to 120,000 people. Since 2016, ~2,000 Tiny Targets have been deployed annually at a cost of USD 471 per km2 per year. Bonon is a degraded forested area and a relatively high number of targets was required as tsetse are present throughout. Nevertheless, the cost comes to only USD 0.5 per person protected per year. Compared to operations using Tiny Targets in Uganda and Chad, the cost was higher per km2 protected, reflecting the need to place targets throughout the area, but low per person protected compared to Chad, highlighting the need to use a range of comparators.

This paper aims to identify the determinants of the length of stay (LoS) of international tourists in Norway. The paper reassesses the standard assumption related to tourists’ LoS; it refers to the travel industry’s current trends, and it postulates a more sustainable approach to analyzing tourists’ LoS at the destination level. The paper concludes with a series of recommendations. The data for this study were collected during 153 data collection days and among 5,300 travelers in Norway. The determinants of LoS were analyzed by means of an ordinary least squares (OLS) regression. The results indicate that tourists’ LoS is positively related to their age, interests (nature-based tourists), origin (German, Dutch tourists) and mode of travel organization (package tourists). A negative and significant effect on tourists’ LoS was found for tourists’ interests (urban-based tourists), spending, and origin (home market, long-haul tourists). No significant results were revealed for two covariates, namely, gender and repeat visitation.

PurposeThe aim of the paper is to identify management practices that are characteristic for SMEs that achieve market success measured by their business performance in last their years of their operation analyze the relationships between management practices applied in small and medium-sized enterprises and their success measured by their business performance drawing on the data from 2710 SMEs operating on the Polish market.Approach/Methodology/DesignA cluster analysis was used to distinguish homogenous SME groups in view of their management practices. We examined differences between groups in terms of their business performance. The HINoV algorithm allowed six variables to be selected out of 32 management practices chosen initially for testing, with these variables providing the basis for grouping. Modal values and medians were calculated for 17 business performance measures in the three clusters produced. The subsequent analysis of those findings was focused on capturing significant differences.FindingsIn the group of 2710 Polish SMEs, it was possible to verify that there existed an association between management practices in the field of modern HRM, computer systems supporting management and the company’s economic performance, as measured by an increase in net revenue and number of customers over the last three years. In clusters where the above mentioned practices were appreciated, modal and median values of the increase reported in net revenue and number of customers were significantly higher.Practical implicationsThe research has shown that at a time marked by a shortage of highly skilled personnel one should pay particular attention to building an integrated and committed team of workers and to employee empowerment. The research has also shown that SME managers monitor only a fraction of basic business performance measures, which may prove to be a major risk to SMEs.Originality/ValuePrevious studies have been largely conducted in a fragmentary manner, i.e. they were concerned with the relationships between the application of some practices (strategic management, BPR, entrepreneurial orientation, monitoring, etc.) and selected business effectiveness measures. In this paper, the research covered SME management practices from a variety of areas which were then compared with the entrepreneurs’ assessment as to whether the company’s economic condition changed over the last three years. It is also the first attempt in post-socialist economies to identify those SME management practices that are related to better economic results.

As the largest carbon dioxide emitter, China is working towards the direction of a green economy. As an irreplaceable part of establishing a green economy, the low-carbon city pilot (LCCP) policy is implemented in many large cities in China, and the scope of implementation will be further expanded. However, to date, there has been an absence of empirical studies basing on prefecture-level cities about the evaluation of China’s LCCP policy. Evaluating and optimizing the LCCP policy is constructive to achieve the goal of China’s green economic transition. In this paper, we evaluated the effect of the LCCP policy on China’s low-carbon economic transition by using the difference-in-difference (DID) approach which can effectively alleviate endogenous problems and better evaluate this effect and the panel data of 210 prefecture-level cities in China from 2008 to 2016. The empirical analysis revealed that the LCCP policy inhibited China’s low-carbon economic transition in general. Specifically, the policy worked well in the eastern region but failed in the central region and western region by studying the regional heterogeneity and influence mechanism. The reason is that the LCCP policy can stimulate low-carbon innovation with the help of innovation offset effects in the eastern region, but it failed to do so in the central region and western region. In addition, this paper analyzed the performance of three types of policy tools adopted by local governments to implement the policy, we found that market-economic tools are valuable to improving the low-carbon economic transition in pilot areas, but command-mandatory tools and voluntary tools have failed to achieve the expected objectives. The research results of this article can provide policy recommendations for optimizing the low-carbon policy and provide a reference for countries that are determined to develop a green economy.

Mathematical models are powerful tools in HIV epidemiology, producing quantitative projections of key indicators such as HIV incidence and prevalence. In order to improve the accuracy of predictions, such models need to incorporate a number of behavioural and biological heterogeneities, especially those related to the sexual network within which HIV transmission occurs. An individual-based model, which explicitly models sexual partnerships, is thus often the most natural type of model to choose. In this paper we present PopART-IBM, a computationally efficient individual-based model capable of simulating 50 years of an HIV epidemic in a large, high-prevalence community in under a minute. We show how the model calibrates within a Bayesian inference framework to detailed age- and sex-stratified data from multiple sources on HIV prevalence, awareness of HIV status, ART status, and viral suppression for an HPTN 071 (PopART) study community in Zambia, and present future projections of HIV prevalence and incidence for this community in the absence of trial intervention., Author summary In this paper we present PopART-IBM, an individual-based model used to simulate HIV transmission in communities in high prevalence settings. We show that PopART-IBM can simulate transmission over a span of decades in a large community in less than a minute. This computational efficiency allows us to calibrate the model within an inference framework, and we show an illustrative example of calibration using an adaptive population Monte Carlo Approximate Bayesian Computation algorithm for a community in Zambia that was part of the HPTN-071 (PopART) trial. We compare the detailed model output to real-world data collected during the trial from this community. Finally, we project how the HIV epidemic would have changed over time in this community if no intervention from the trial had occurred.

The prevalence of dyslexia identification has increased significantly over the last two decades. Yet there is debate over whether there are distinct biological and cognitive differences between those with literacy difficulties and the subgroup of people identified as dyslexic. This is the first paper that provides evidence for this ongoing debate by investigating the socio-demographic factors, outside biology and cognition, that predict whether a child is identified as dyslexic in the UK. Using secondary data from the UK’s Millennium Cohort Study, this paper examines the socio-demographic factors that predict whether a child’s teacher identifies them as dyslexic at age 11. Gender, season of birth, socio-economic class and parental income are found to be significant predictors of the dyslexia label. Therefore, factors seemingly unrelated to the clinical aspects of dyslexia influence whether a child is identified as dyslexic in England and Wales. This suggests that label may not be evenly distributed across a population; furthermore, it may also indicate that resources for support may not be fairly allocated. The findings further support the argument that a ‘dyslexic sub-group’ within poor readers is created due to the impact of environmental factors. The results from this national-scale study thus questions the reliability, validity and moral integrity of the allocation of the dyslexia label across current education systems in the UK.

Depending on the strategy of "Healthy China", more and more people pay attention to health issues. The integration and development of sports industry and health service industry is an inevitable outcome of industrial transformation and upgrading and healthy life in the new era. Through constructing the evaluation index system of the coupling and coordination development degree between sports industry and health service industry, using entropy evaluation method and coupling and coordination degree model, this paper explore the comprehensive level and coupling and coordination development status of sports industry and health service industry in thirty-one provinces, municipality cities and autonomous regions of China from 2013 to 2017. The results of this paper show that the comprehensive China’s sports industry and health service industry both present an incremental development trend year by year, and are characterized by the distribution of "high in the east and low in the west" in space. The government’s policy support provides superior industrial supporting conditions for the development of sports industry. However, it is not conducive to the promotion of industrial economic benefits. In the health service industry, the rapid development of health insurance is beneficial to the integration of industrial resources and the perfection of industrial chain. Whereas as the core content of health service industry, health service has greater space for development; the coupling and coordination degree between the two industries rises from mild maladjustment to basic coordination, which is characterized by the distribution of "high in the east and low in the west" in space; among provinces, with Beijing, the Yangtze River Delta and Guangdong as the three development center points, it shows the spatial evolutionary process from "dispersion-type plaques" to "gathering type scattered surfaces".

Apple (Malus domestica), is one of the most important fruit trees cultivated in temperate regions but, newly introduced in Uganda for its income and nutritional importance. However, apples are found to be susceptible to arthropod pests, some known to cause damages on both the plant and fruits. Some of these insect pests are known while others are still unknown and could be effectively managed through integrated pest management methods. For any effective Integrated insect Pest Management, it is necessary to have enough information about the biology and ecology of a given pest, including, spatial distribution and factors that affect pest species’ distribution. Therefore, in this paper, systematic information on insect pests damaging apple fruit trees was reviewed. Different recent literature on insect pests hosted by apples under different agroecological systems of the world was reviewed. The review focused on classifying common insect pests, preferred varieties and their ecological distribution. This was achieved by using the ISI Web of Science bibliographic database and search terms such as apple entomofauna and insect pests were used, with specific keywords of [apple*] AND [insect*] AND [pest]. It was found out that, insect pests in apples belong to several groups of invasive pests which include Coleoptera and Polydrusus (beetles, weevils), Diptera (leaf, seed, fruit flies), Hemiptera (aphids, psyllids, bugs and scales), Hymenoptera (sawflies, wasps ants, bees), Thysanoptera (thrips), Trombidiformes (mites) and Lepidoptera (moths and butterflies) that are of economic value. This work, again reveals dramatic rates of appearance of isect pests in orchards in Africa and elsewhere, which have compromised apple industry’s growth. The review pieced together known information about the insect pests that occurs in apples in different geographical locations. But, information on insect pest in Uganda’s apple orchards remained scanty, which calls for an immediate detailed study on the same.

This paper contributes to the lack of longitudinal studies concerning online information access to corporate governance (CG) practices in the banking sector of Latin American countries. In particular, this study aims to analyze the factors that influence information transparency, both mandatory and voluntary, related to CG practices of banks that operate in Paraguay via their websites from 2016 to 2019. Findings indicate the need to improve the level of information available on websites, with disclosure of voluntary information on CG practices being more prevalent than the disclosure of mandatory information. Likewise, banks that operate in Paraguay have made scant “progress” regarding online access to their governance information over the years analyzed. Moreover, the factors “Bank size” and “listed status” positively influence the information transparency regarding CG practices of Paraguayan banks. In contrast, “leverage,” “liquidity,” “size of the audit firm,” and “credit risk rating” are factors that have a negative relation with the extent of CG disclosure.

Agriculture is a very important sector of the economy that has a great influence on rural areas. Almost sixty years of the Common Agricultural Policy (CAP) in the European Union (EU) may impose a question on the impact of this policy on job creation and economic growth in rural areas. By analyzing key indicators, one should note that although there are still many problems to tackle, the CAP has been successful to some extend in increasing employment rate and Gross Domestic Product (GDP) per capita as well as decreasing poverty rate in the EU rural areas. There are also more and more households connected to the next-generation broadband network and there is still a significant number of bed places in the EU rural areas. Although, the situation in specific EU Member States and their rural regions may be different, the overall performance of the EU is satisfactory and shows positive prognostics for the current EU financial perspective of 2021–2027. This paper also provides an empirical approach which checks whether there is a connection between the employment rate and the rural development measured in GDP per capita based on the data from the Baltic States: Estonia, Latvia and Lithuania in the period of 2000–2020. This research confirms that when increasing the level of rural employment, the economic growth rises in rural areas.

This paper examines whether mega-events-initiated planning regulations improved air quality in Chinese cities and explores the driving forces of the enforcement of such regulations. Using the 2008 Beijing Olympics as an example, we find that mega-events serve as an opportunity for cities to combat air pollution. The 2008 Olympics prompted a handful of Chinese cities to cut pollution and sustain a blue sky: Cities with air quality regulated for the Olympics cut their Air Pollution Index by about 16 points during the Games, compared to non-regulated cities, and 60% of that effect remained four years after the event. These achievements are obtained through effective mobilization of city leaders by associating air quality with their political careers. This study reveals that 1) a mega-event may improve urban environmental quality beyond the host cities and the event period, and 2) successful implementation of environmental regulations hinges on incentivizing local leaders.

Biocapacity of a region exhibits spatial differences owing to the limitations of regional scale and natural conditions. Based on the multi-scale perspective, we comprehensively studied and analyzed the temporal and spatial differences of the biocapacity of a region in an attempt to establish the groundwork for optimizing urban development and its utilization framework. By adopting the ecological footprint model along with multi-scale difference evaluation method, the municipal and county scales are incorporated into a unified analysis framework in this paper, thereby facilitating the exploration of the temporal and spatial differences in the biocapacity of Shenyang—a city in China—from 2005 to 2019. The results demonstrated that: 1) At the municipal scale, the biocapacity per capita fluctuated between 1.35 hm2/person and 2.22 hm2/person. It revealed an “up-down-up” trend, which appeared consistent with the Kuznets cycle; at the county scale, the biocapacity depicted spatial differences, while those of downtown and surrounding districts/counties developed a two-level ascending hierarchical structure. 2) The time series of footprint size and depth first ascended and then declined, and can be classified into four types: closed type, inverted U-type, S-type, and M-type. Among them, S-type and M-type have the phenomenon of over-utilizing the stock capital. 3) For a long time, the regional difference of biocapacity has mostly dwelt on two scales with an evident scale effect, and the biocapacity of Liaozhong District was the worst.

Cocoa is a plant with origins in northwestern South America with high relevance in the global economy. Evidence indicates that cocoa is sensitive to a dry climate, under which crop production is reduced. Projections for future climate change scenarios suggest a warmer and drier climate in the Amazon basin. In this paper, we quantify the potential effects in cocoa production due to its edaphoclimatic suitability changes to the Brazilian Amazon biome and account for regional differences in planning occupation territories. We modeled the suitability of cocoa’s geographical distribution using an ensemble of 10 correlative models that were run in the “biomod2” library and projected to two future climate scenarios (RCPs 4.5 and 8.5) by 2050. Combining information on climate and soil suitability and installed infrastructure in the macro-regions of the Brazilian Amazon. We defined a zoning system to indicate how cocoa production may respond to climate change according to the current and future suitability model. Our results suggest that a reduction in precipitation and an increase in temperature may promote a reduction in the suitability of cocoa production in the Brazilian Amazon biome. In addition of the areas suitable for cocoa plantation, we found a 37.05% and 73.15% decrease in the areas suitable for intensification and expansion zones under RCP 4.5 and 8.5, respectively, compared with the current scenario. We conclude that there may be a need to expand land to cocoa production in the future, or else it will be necessary to plant a cocoa variety resistant to new climatic conditions. Besides, we recommend procedures to combat illegal deforestation to prevent the most critical climate change scenarios from occurring.

To undertake a reliable analysis of injury severity in road traffic accidents, a complete understanding of important attributes is essential. As a result of the shift from traditional statistical parametric procedures to computer-aided methods, machine learning approaches have become an important aspect in predicting the severity of road traffic injuries. The paper presents a hybrid feature selection-based machine learning classification approach for detecting significant attributes and predicting injury severity in single and multiple-vehicle accidents. To begin, we employed a Random Forests (RF) classifier in conjunction with an intrinsic wrapper-based feature selection approach called the Boruta Algorithm (BA) to find the relevant important attributes that determine injury severity. The influential attributes were then fed into a set of four classifiers to accurately predict injury severity (Naive Bayes (NB), K-Nearest Neighbor (K-NN), Binary Logistic Regression (BLR), and Extreme Gradient Boosting (XGBoost)). According to BA’s experimental investigation, the vehicle type was the most influential factor, followed by the month of the year, the driver’s age, and the alignment of the road segment. The driver’s gender, the presence of a median, and the presence of a shoulder were all found to be unimportant. According to classifier performance measures, XGBoost surpasses the other classifiers in terms of prediction performance. Using the specified attributes, the accuracy, Cohen’s Kappa, F1-Measure, and AUC-ROC values of the XGBoost were 82.10%, 0.607, 0.776, and 0.880 for single vehicle accidents and 79.52%, 0.569, 0.752, and 0.86 for multiple-vehicle accidents, respectively.

The Indonesian government launched various programs to handle stunting cases, including village funds. This paper examined the effects of village fund programs and village apparatuses’ capacities to combat stunting based on aggregate data at the district level in Indonesia. Using descriptive data analysis and fixed effect panel regression, we observed that village fund programs could significantly reduce Indonesia’s stunting prevalence, especially outside Java. It also revealed that the increasing education of regional leaders does not necessarily positively impact leaders’ skills in handling stunting. At the same time, the number of village officials has a statistically significant influence on reducing stunting prevalence. It advised that the village budget fund can support national priorities in tackling the prevalence of stunting. Furthermore, it is essential to build the capacity of the village head for increasing awareness of health activities, especially early prevention of stunting, in addition to an adequate number of officials.

Made available in DSpace on 2022-04-28T19:49:42Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-01-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Several studies have reported the relationship of deforestation with increased incidence of infectious diseases, mainly due to the deregulation caused in these environments. The purpose of this study was to answer the following questions: a) is increased loss of vegetation related to dengue cases in the Brazilian Cerrado? b) how do different regions of the tropical savanna biome present distinct patterns for total dengue cases and vegetation loss? c) what is the projection of a future scenario of deforestation and an increased number of dengue cases in 2030? Thus, this study aimed to assess the relationship between loss of native vegetation in the Cerrado and dengue infection. In this paper, we quantify the entire deforested area and dengue infection cases from 2001 to 2019. For data analyses, we used Poisson generalized linear model, descriptive statistics, cluster analysis, non-parametric statistics, and autoregressive integrated moving average (ARIMA) models to predict loss of vegetation and fever dengue cases for the next decade. Cluster analysis revealed the formation of four clusters among the states. Our results showed significant increases in loss of native vegetation in all states, with the exception of Piauí. As for dengue cases, there were increases in the states of Minas Gerais, São Paulo, and Mato Grosso. Based on projections for 2030, Minas Gerais will register about 4,000 dengue cases per 100,000 inhabitants, São Paulo 750 dengue cases per 100,000 inhabitants, and Mato Grosso 500 dengue cases per 100,000 inhabitants. To reduce these projections, Brazil will need to control deforestation and implement public health, environmental and social policies, requiring a joint effort from all spheres of society. Graduate Program in Agronomy–Cropping Systems São Paulo State University (Unesp), SP Graduate Program in Geography São Paulo State University (Unesp) School of Technology and Sciences, SP Federal University of Mato Grosso do Sul (UFMS), Chapadão do Sul, MS Federal University of Acre (UFAC) Graduate Program in Agronomy State University of Londrina (Uel), PR Graduate Program in Sciences—Nuclear Energy in Agriculture Centro de Energia Nuclear na Agricultura São Paulo University São Paulo State University (Unesp) Engineering School, SP Graduate Program in Geography Federal University of Mato Grosso do Sul (UFMS), Três Lagoas, MS Graduate Program in Agronomy–Cropping Systems São Paulo State University (Unesp), SP Graduate Program in Geography São Paulo State University (Unesp) School of Technology and Sciences, SP São Paulo State University (Unesp) Engineering School, SP CNPq: 303767/2020-0

Hemorrhagic fever with renal syndrome (HFRS) is a zoonosis characterized by clinical features of high fever, hemorrhage, and renal damage. China has the largest number of HFRS cases worldwide, accounting for over 90% of the total reported cases. In this paper, we used surveyed HFRS data and satellite imagery to conduct geostatistical analysis for investigating the associations of rapid urbanization, water bodies, and other factors on the spatiotemporal dynamics of HFRS from year 2005 to 2018 in Xi’an City, Northwest China. The results revealed an evident epidemic aggregation in the incidence of HFRS within Xi’an City with a phenomenal fluctuation in periodic time series. Rapid urbanization was found to greatly affect the HFRS incidence in two different time phases. HFRS caused by urbanization influences farmers to a lesser extent than it does to non-farmers. The association of water bodies with the HFRS incidence rate was found to be higher within the radii of 696.15 m and 1575.39 m, which represented significant thresholds. The results also showed that geomatics approaches can be used for spatiotemporally investigating the HFRS dynamic characteristics and supporting effective allocations of resources to formulate strategies for preventing epidemics., Author summary Hemorrhagic fever with renal syndrome (HFRS) is an infectious disease transmitted by the infected reservoir hosts, which chiefly include rodents, shrews, and moles. The mechanism of HFRS infection is determined by a complex interplay of various natural and socioeconomic factors. Previous studies have identified a close relationship between urbanization processes and HFRS transmission dynamics. However, the relationship involves a dual response and has not yet been quantitatively identified. This research aimed to spatiotemporally characterize how rapid urbanization affects the dynamics of HFRS. In addition, the role of water bodies, vegetation, rainfall, and occupation types in epidemic transmissions has also not been adequately investigated at the interurban scale over a long time period. Therefore, we analyzed the spatiotemporal association between the distributions of water bodies and HFRS infections and also investigated the interactions between urbanization, water body, vegetation, rainfall, and different occupation types by using multi-source data through both traditional statistical and geospatial techniques. Our work revealed biphasic associations among HFRS infection with both rapid urbanization and distribution of water bodies. Hence, it can provide useful information to formulate effective strategies for the prevention and control of HFRS.

Using microdata from the Chinese General Social Survey (CGSS 2010), this paper investigates whether there are green returns to education in China, where educational attainment promotes pro-environmental attitudes and behaviors. We establish causality by exploiting the exogenous variation induced by the implementation of the Compulsory Schooling Law (CSL) in China. We find evidence that educational attainment is associated with higher levels of pro-environmental attitudes and behaviors, and these estimates are robust to various robustness checks. Further analysis reveals that the acquisition of environmental knowledge is the channel that drives the effect of education on pro-environmental attitudes and behaviors. Finally, the effects of education are heterogeneous across individuals.

Background “Contracting Out” is a popular strategy to expand coverage and utilization of health services. Bangladesh began contracting out primary healthcare services to NGOs in urban areas through the Urban Primary Health Care Project (UPHCP) in 1998. Over the three phases of this project, retention of trained and skilled human resources, especially doctors, proved to be an intractable challenge. This paper highlights the issues influencing doctor’s retention both in managerial as well as service provision level in the contracted-out setting. Methodology In this qualitative study, 42 Key Informant Interviews were undertaken with individuals involved with UPHCP in various levels including relevant ministries, project personnel representing the City Corporations and municipalities, NGO managers and doctors. Verbatim transcripts were coded in ATLAS.ti and analyzed using the thematic analysis. Document review was done for data triangulation. Results The most cited problem was a low salary structure in contrast to public sector pay scale followed by a dearth of other financial incentives such as performance-based incentives, provident funds and gratuities. Lack of career ladder, for those in both managerial and service delivery roles, was also identified as a factor hindering staff retention. Other disincentives included inadequate opportunities for training to improve clinical skills, ineffective staffing arrangements, security issues during night shifts, abuse from community members in the context of critical patient management, and lack of job security after project completion. Conclusions An adequate, efficient and dedicated health workforce is a pre-requisite for quality service provision and patient utilization of these services. Improved career development opportunities, the provision of salaries and incentives, and a safer working environment are necessary actions to retain and motivate those serving in managerial and service delivery positions in contracting out arrangements.

Objective The Spanish health system is made up of seventeen regional health systems. Through the official reporting systems, some inconsistencies and differences in case fatality rates between Autonomous Communities (CC.AA.) have been observed. Therefore the objective of this paper is to compare COVID-19 case fatality rates across the Spanish CC.AA. Material and methods Observational descriptive study. The COVID-19 case fatality rate (CFR) was estimated according to the official records (CFR-PCR+), the daily mortality monitory system (MoMo) record (CFR-Mo), and the seroprevalence study ENE-COVID-19 (Estudio Nacional de sero Epidemiologia Covid-19) according to sex, age group and CC.AA. between March and June 2020. The main objective is to detect whether there are any differences in CFR between Spanish Regions using two different register systems, i. e., the official register of the Ministry of Health and the MoMo. Results Overall, the CFR-Mo was higher than the CFR-PCR+, 1.59% vs 0.98%. The differences in case fatality rate between both methods were significantly higher in Castilla La Mancha, Castilla y León, Cataluña, and Madrid. The difference between both methods was higher in persons over 74 years of age (CFR-PCR+ 7.5% vs 13.0% for the CFR-Mo) but without statistical significance. There was no correlation of the estimated prevalence of infection with CFR-PCR+, but there was with CFR-Mo (R2 = 0.33). Andalucía presented a SCFR below 1 with both methods, and Asturias had a SCFR higher than 1. Cataluña and Castilla La Mancha presented a SCFR greater than 1 in any scenario of SARS-CoV-2 infection calculated with SCFR-Mo. Conclusions The PCR+ case fatality rate underestimates the case fatality rate of the SARS-CoV- 2 virus pandemic. It is therefore preferable to consider the MoMo case fatality rate. Significant differences have been observed in the information and registration systems and in the severity of the pandemic between the Spanish CC.AA. Although the infection prevalence correlates with case fatality rate, other factors such as age, comorbidities, and the policies adopted to address the pandemic can explain the differences observed between CC.AA.

Understanding how textual information impacts financial market volatility has been one of the growing topics in financial econometric research. In this paper, we aim to examine the relationship between the volatility measure that is extracted from GARCH modelling and textual news information both publicly available and from subscription, and the performances of the two datasets are compared. We utilize a latent Dirichlet allocation method to capture the dynamic features of the textual data overtime by summarizing their statistical outputs, such as topic distributions in documents and word distributions in topics. In addition, we transform various measures representing the popularity and diversity of topics to form predictors for a rolling regression model to assess the usefulness of textual information. The proposed method captures the statistical properties of textual information over different time periods and its performance is evaluated in an out-of-sample analysis. Our results show that the topic measures are more useful for predicting our volatility proxy, the unexplained variance from the GARCH model than the simple moving average. The finding indicates that our method is helpful in extracting significant textual information to improve the prediction of stock market volatility.

The Danube is promoted as a pan-European river, what can be justified for instance by the vast range of its drainage basin, covering 19 countries on both sides of the historical border diving Eastern and Western Europe. Differentiation of imaginations of Danube course from the perspective of 7 European cities, based on research covering 1577 respondents, conducted between 2005–2007 and 2016–2018 has been presented in the paper. Maps presenting the generalized imagination of river course have been generated for each city. It has been proved that in spite of substantial political, economical and symbolical importance of this river for big part of Europe, the course of Danube remains unknown for inhabitants of its Western part, in parallel to more correct recognition of the river by students from Eastern Europe. It has been shown that the perception does not change despite the progressing integration processes.

Background With the increase in elderly population, the risk of cardiovascular diseases (CVD) among Indian older adults is also increasing. The present paper tries to assess how different anthropometric measures of obesity and physical activity affects cardiovascular disease risk among older adults in India. Methods The data from Longitudinal Ageing Study in India (LASI) has been used. The total sample size for the present study is 31,464 older adults aged 60 years and above. Chi-square test and binary logistic regression has been used to measure the association of obesity measures and CVD prevalence. Results About 35.2% (n = 11,058) of the older adults suffered from CVD. Moreover, 22.2% (n = 6,217) of the older adults were obese/overweight, 23.7% (n = 6,651) had high risk waist circumference and 77.0% (n = 21,593) had high risk waist-Hip ratio. The likelihood of CVD was 60%, 50%, and 34% significantly higher among older adults who were obese/overweight [Adjusted odds ratio (AOR): 1.60; CI: 1.48–1.72], had high risk waist circumference [AOR: 1.50; CI: 1.39–1.62] and high risk waist-Hip ratio [AOR: 1.34; CI: 1.25–1.44], respectively compared to older adults with normal BMI and those who do not have a high risk waist circumference and high risk waist hip ratio. Moreover, older adults who never did physical activity had 22 per cent higher risk of CVD than those who did frequent [AOR: 1.22; CI: 1.13–1.32] physical activity. Conclusion The burden of overweight and obesity along with physical inactivity increases the risk of CVD in older adults. These findings highlight the urgent need for framing direct and indirect strategies to control obesity in order to reduce the burden of CVD among older adults in India.

Antimicrobial resistance (AMR) is a global public health crisis that is now impacted by the COVID-19 pandemic. Little is known how COVID-19 risks influence people to consume antibiotics, particularly in contexts like Bangladesh where these pharmaceuticals can be purchased without a prescription. This paper identifies the social drivers of antibiotics use among home-based patients who have tested positive with SARS-CoV-2 or have COVID-19-like symptoms. Using qualitative telephone interviews, the research was conducted in two Bangladesh cities with 40 participants who reported that they had tested positive for coronavirus (n = 20) or had COVID-19-like symptoms (n = 20). Our analysis identified five themes in antibiotic use narratives: antibiotics as ‘big’ medicine; managing anxiety; dealing with social repercussions of COVID-19 infection; lack of access to COVID-19 testing and healthcare services; and informal sources of treatment advice. Antibiotics were seen to solve physical and social aspects of COVID-19 infection, with urgent ramifications for AMR in Bangladesh and more general implications for global efforts to mitigate AMR.

Background Digital health (DH) and the benefits of related services are fairly well understood. However, it still is critical to map the digital health care landscape including the key elements that define it as an ecosystem. Particularly, knowing the perspectives of citizens on this digital transformation is an important angle to capture. In this review we aim to analyze the relevant studies to identify how DH is understood and experienced by Australian citizens and what they may require from DH platforms. Materials and methods A scoping literature review was conducted across several electronic databases (ACM Digital Library, OVID, PubMed, Scopus, IEEE, Science Direct, SAGE), as well as grey literature. Additionally, citation mining was conducted to identify further relevant studies. Identified studies were subjected to eligibility criteria and the final set of articles was independently reviewed, analyzed, discussed and interpreted by three reviewers. Results Of 3811 articles, 98 articles met the inclusion criteria with research-based articles–as opposed to review articles or white papers– comprising the largest proportion (72%) of the selected literature. The qualitative analysis of the literature revealed five key elements that capture the essence of the digital health ecosystem interventions from the viewpoint of the Australian citizens. The identified elements were “consumer/user”, “health care”, “technology”, “use and usability”, “data and information”. These elements were further found to be associated with 127 subcategories. Conclusions This study is the first of its kind to analyze and synthesize the relevant literature on DH ecosystems from the citizens’ perspective. Through the lens of two research questions, this study defines the key components that were found crucial to understanding citizens’ experiences with DH. This understanding lays a strong foundation for designing and fostering DH ecosystem. The results provide a solid ground for empirical testing.

In this paper we assess the impact of the recent European recession on stillbirth indices over the course of the 2000s and 2010s; the analysis focuses on four Southern European countries (Greece, Italy, Spain, Portugal), which were seriously affected by the sovereign debt crisis from around 2008 to 2017. We use national vital statistics and established economic indicators for the period 2000–2017; stillbirth ratios (stillbirths per 1000 livebirths) are the chosen response variable. For the purpose of the study, we employ correlation analysis and fit regression models. The overall impact of economic indicators on the stillbirth indices is sizeable and statistically robust. We find that a healthy economy is associated with low and declining levels of stillbirth measures. In contrast, economic recession appears to have an adverse effect (Greece, Italy and Spain), or an unclear impact (Portugal), on the stillbirth outcome. This study provides evidence of the adverse effect of the European sovereign debt crisis and ensuing period of austerity on a scarcely explored aspect of health.

Detail is a double edged sword in epidemiological modelling. The inclusion of mechanistic detail in models of highly complex systems has the potential to increase realism, but it also increases the number of modelling assumptions, which become harder to check as their possible interactions multiply. In a major study of the Covid-19 epidemic in England, Knock et al. (2020) fit an age structured SEIR model with added health service compartments to data on deaths, hospitalization and test results from Covid-19 in seven English regions for the period March to December 2020. The simplest version of the model has 684 states per region. One main conclusion is that only full lockdowns brought the pathogen reproduction number, R, below one, with R ≫ 1 in all regions on the eve of March 2020 lockdown. We critically evaluate the Knock et al. epidemiological model, and the semi-causal conclusions made using it, based on an independent reimplementation of the model designed to allow relaxation of some of its strong assumptions. In particular, Knock et al. model the effect on transmission of both non-pharmaceutical interventions and other effects, such as weather, using a piecewise linear function, b(t), with 12 breakpoints at selected government announcement or intervention dates. We replace this representation by a smoothing spline with time varying smoothness, thereby allowing the form of b(t) to be substantially more data driven, and we check that the corresponding smoothness assumption is not driving our results. We also reset the mean incubation time and time from first symptoms to hospitalisation, used in the model, to values implied by the papers cited by Knock et al. as the source of these quantities. We conclude that there is no sound basis for using the Knock et al. model and their analysis to make counterfactual statements about the number of deaths that would have occurred with different lockdown timings. However, if fits of this epidemiological model structure are viewed as a reasonable basis for inference about the time course of incidence and R, then without very strong modelling assumptions, the pathogen reproduction number was probably below one, and incidence in substantial decline, some days before either of the first two English national lockdowns. This result coincides with that obtained by more direct attempts to reconstruct incidence. Of course it does not imply that lockdowns had no effect, but it does suggest that other non-pharmaceutical interventions (NPIs) may have been much more effective than Knock et al. imply, and that full lockdowns were probably not the cause of R dropping below one.

The slowdown of China’s economic growth in the middle-income stage has caused widespread concerns. Based on the analysis of economic structures to explain the downward trend of economic growth, this study expanded the Solow-Swan model to investigate the structural imbalances and evaluated their impacts during the structural transformation in different stages and regions on the economic downturn. Considering the processes of production, distribution, and consumption, six structures were chosen for national and prefecture-levels in China from 1997 to 2017, including sectoral structure, population structure, investment and consumption structure, import-export structure, urban-rural income structure, and financial structure. The study found that China’s comprehensive economic structure was significantly different before and after the middle-income stage, and structural bonus tended to decline. Structural imbalance presented a U-shaped pattern of decreasing first and then increasing, and the impact on economic growth underwent stages of suppression-promotion-suppression. There was a significant difference in the imbalance of six sub-structures and their impacts; furthermore, in the four regions of east, center, west, and northeast the observations were very different. Taken together, the imbalance of economic structure and economic transformation coexisted, and the economic growth slowed down. Based on the experiences from China, this paper provided some evidence for promoting structural optimization and transformation.

West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input.

Substandard and falsified (SF) antimalarials have devastating consequences including increased morbidity, mortality and economic losses. Portable medicine quality screening devices are increasingly available, but whether their use for the detection of SF antimalarials is cost-effective is not known. We evaluated the cost-effectiveness of introducing such devices in post-market surveillance in pharmacies in Laos, conservatively focusing on their outcome in detecting SF artemisinin-based combination therapies (ACTs). We simulated the deployment of six portable screening devices: two handheld near-infrared [MicroPHAZIR RX, NIR-S-G1], two handheld Raman [Progeny, TruScan RM]; one portable mid-infrared [4500a FTIR] spectrometers, and single-use disposable paper analytical devices [PADs]. We considered two scenarios with high and low levels of SF ACTs. Different sampling strategies in which medicine inspectors would test 1, 2, or 3 sample(s) of each brand of ACT were evaluated. Costs of inspection including device procurement, inspector time, reagents, reference testing, and replacement with genuine ACTs were estimated. Outcomes were measured as disability adjusted life years (DALYs) and incremental cost-effectiveness ratios were estimated for each device compared with a baseline of visual inspections alone. In the scenario with high levels of SF ACTs, all devices were cost-effective with a 1-sample strategy. In the scenario of low levels of SF ACTs, only four devices (MicroPHAZIR RX, 4500a FTIR, NIR-S-G1, and PADs) were cost-effective with a 1-sample strategy. In the multi-way comparative analysis, in both scenarios the NIR-S-G1 testing 2 samples was the most cost-effective option. Routine inspection of ACT quality using portable screening devices is likely to be cost-effective in the Laos context. This work should encourage policy-makers or regulators to further investigate investment in portable screening devices to detect SF medicines and reduce their associated undesired health and economic burdens., Author summary Distribution of poor quality medicines are an increasing global concern, especially in low- and middle-income countries (LMICs) where the effectiveness of antimicrobials can be a matter of life-or-death for patients with malaria and other potentially fatal infectious diseases. Substandard and falsified antimalarial drugs, including artemisinin-based combination therapies are widely distributed across LMICs. This endangers patients and in the longer term threatens malaria control and elimination campaigns by promoting the development of drug resistance. New field detection devices are increasingly available and could enhance the inspection process with prompt and actionable, real-time results. We conducted a cost-effectiveness analysis of the implementation of six portable devices for medicine quality screening during pharmacy post-market surveillances in Laos. This analysis conservatively focused only on the benefits of these devices in detecting substandard and falsified artemisinin-based combination therapies (ACTs), measured in terms of health outcomes for malaria patients obtaining treatment from pharmacies. Our findings suggest that using these portable devices for routine surveillance of ACT quality is likely to be cost-effective. Policy-makers and regulators might therefore consider investment in these field detection devices to minimise undesired health and economic burdens associated with substandard and falsified medicines.

Data Availability: All relevant data are within the paper and its Supporting Information files: Self-employment intention questionnaire (available at: https://figshare.com/articles/journal_contribution/Self-employment_intention_questionnaire_/16612528); Data used in the study (available at Data used in the study). Copyright: © 2021 Al-Qadasi et al.. This study assesses whether final-year undergraduate students at Sana’a University, Yemen intend to start their own business. The study employs the theory of planned behaviour and two environmental factors to explore whether the theory’s behavioural factors and the contextual factors of Lüthje & Franke’s model have an impact on students’ intentions to start their own business. A questionnaire survey with a random sample of 335 final-year university students from the largest public university in Yemen has been conducted. Data has been analysed using descriptive statistics, Pearson’s correlation and structural equation modelling. The findings indicate that students’ perceptions of entrepreneurship have a strong, direct impact on self-employment intention, excluding social norms and entrepreneurial self-efficacy. Students’ self-employment intention is directly affected by perceived barriers and support factors in the entrepreneurship-related context. To increase their entrepreneurial abilities, university students require more training and education to be able to start new businesses. Developing entrepreneurial skills among citizens may improve the societal norms of business. The outcomes provide significant implications for policymakers, academic communities and international bodies. Jilin University

We construct a recursive Bayesian smoother, termed EpiFilter, for estimating the effective reproduction number, R, from the incidence of an infectious disease in real time and retrospectively. Our approach borrows from Kalman filtering theory, is quick and easy to compute, generalisable, deterministic and unlike many current methods, requires no change-point or window size assumptions. We model R as a flexible, hidden Markov state process and exactly solve forward-backward algorithms, to derive R estimates that incorporate all available incidence information. This unifies and extends two popular methods, EpiEstim, which considers past incidence, and the Wallinga-Teunis method, which looks forward in time. We find that this combination of maximising information and minimising assumptions significantly reduces the bias and variance of R estimates. Moreover, these properties make EpiFilter more statistically robust in periods of low incidence, where several existing methods can become destabilised. As a result, EpiFilter offers improved inference of time-varying transmission patterns that are advantageous for assessing the risk of upcoming waves of infection or the influence of interventions, in real time and at various spatial scales., Author summary Inferring changes in the transmissibility of an infectious disease is crucial for understanding and controlling epidemic spread. The effective reproduction number, R, is widely used to assess transmissibility. R measures the average number of secondary cases caused by a primary case and has provided insight into many diseases including COVID-19. An upsurge in R can forewarn of upcoming infections, while suppression of R can indicate if public health interventions are working. Reliable estimates of temporal changes in R can contribute important evidence to policymaking. Popular R-inference methods, while powerful, can struggle when cases are few because data are noisy. This can limit detection of crucial variations in transmissibility that may occur, for example, when infections are waning or when analysing transmissibility over fine geographic scales. In this paper we improve the general reliability of R-estimates and specifically increase robustness when cases are few. By adapting principles from control engineering, we formulate EpiFilter, a novel method for inferring R in real time and retrospectively. EpiFilter can potentially double the information extracted from epidemic time-series (when compared to popular approaches), significantly filtering the noise within data, to minimise both bias and uncertainty of R-estimates and enhance the detection of salient change-points in transmissibility.

Background Leprosy elimination primarily targets transmission of Mycobacterium leprae which is not restricted to patients’ households. As interruption of transmission is imminent in many countries, a test to detect infected asymptomatic individuals who can perpetuate transmission is required. Antibodies directed against M. leprae antigens are indicative of M. leprae infection but cannot discriminate between active and past infection. Seroprevalence in young children, however, reflects recent M. leprae infection and may thus be used to monitor transmission in an area. Therefore, this literature review aimed to evaluate what has been reported on serological tests measuring anti-M. leprae antibodies in children without leprosy below the age of 15 in leprosy-endemic areas. Methods and findings A literature search was performed in the databases Pubmed, Infolep, Web of Science and The Virtual Health Library. From the 724 articles identified through the search criteria, 28 full-text articles fulfilled all inclusion criteria. Two additional papers were identified through snowballing, resulting in a total of 30 articles reporting data from ten countries. All serological tests measured antibodies against phenolic glycolipid-I or synthetic derivatives thereof, either quantitatively (ELISA or UCP-LFA) or qualitatively (ML-flow or NDO-LID rapid test). The median seroprevalence in children in endemic areas was 14.9% and was stable over time if disease incidence remained unchanged. Importantly, seroprevalence decreased with age, indicating that children are a suitable group for sensitive assessment of recent M. leprae infection. However, direct comparison between areas, solely based on the data reported in these studies, was impeded by the use of different tests and variable cut-off levels. Conclusions Quantitative anti-PGL-I serology in young children holds promise as a screening test to assess M. leprae infection and may be applied as a proxy for transmission and thereby as a means to monitor the effect of (prophylactic) interventions on the route to leprosy elimination., Author summary Leprosy, a chronic infectious disease caused by Mycobacterium leprae (M. leprae), targets the skin and nerves and often results in irreversible disabilities as well as social exclusion. Though the disease can be efficiently treated, leprosy elimination is hampered by ongoing transmission of M. leprae. Currently, elimination is monitored by the number of new cases. Since only a small percentage of individuals infected with M. leprae develops disease, this does not accommodate monitoring of transmission. Previous studies have shown that antibody levels against M. leprae in blood correspond to the bacterial load in an individual and can be used as a proxy for infection, although antibodies cannot distinguish between past and present infection. In young children, infection is recent by definition, which allows assessment of more current state of transmission in an area. Thus, this literature review investigated studies on leprosy serology in children without leprosy. Our findings underscore that young children are a fitting group for up-to-date monitoring of M. leprae transmission in an area as seropositivity is inversely related with age. Importantly, a standardized, field-friendly test quantitatively measuring anti-M. leprae antibodies should be applied for population screening to monitor the status of transmission and thereby elimination in an area.

Avian influenza A viruses (IAVs) pose risks to public, agricultural, and wildlife health. Bridge hosts are spillover hosts that share habitat with both maintenance hosts (e.g., mallards) and target hosts (e.g., poultry). We conducted a comprehensive assessment of European starlings (Sturnus vulgaris), a common visitor to both urban and agricultural environments, to assess whether this species might act as a potential maintenance or bridge host for IAVs. First, we experimentally inoculated starlings with a wild bird IAV to investigate susceptibility and replication kinetics. Next, we evaluated whether IAV might spill over to starlings from sharing resources with a widespread IAV reservoir host. We accomplished this using a specially designed transmission cage to simulate natural environmental transmission by exposing starlings to water shared with IAV-infected mallards (Anas platyrhynchos). We then conducted a contact study to assess intraspecies transmission between starlings. In the initial experimental infection study, all inoculated starlings shed viral RNA and seroconverted. All starlings in the transmission study became infected and shed RNA at similar levels. All but one of these birds seroconverted, but detectable antibodies were relatively transient, falling to negative levels in a majority of birds by 59 days post contact. None of the contact starlings in the intraspecies transmission experiment became infected. In summary, we demonstrated that starlings may have the potential to act as IAV bridge hosts if they share water with IAV-infected waterfowl. However, starlings are unlikely to act as maintenance hosts due to limited, if any, intraspecies transmission. In addition, starlings have a relatively brief antibody response which should be considered when interpreting serology from field samples. Further study is needed to evaluate the potential for transmission from starlings to poultry, a possibility enhanced by starling’s behavioral trait of forming very large flocks which can descend on poultry facilities when natural resources are scarce., Author summary Besides causing seasonal influenza, influenza A viruses (IAVs) are important because they can become pathogenic and threaten human, livestock, or wildlife health. Wild birds are the primary reservoir of IAVs which are generally low pathogenic, but when wild bird viruses spill over into poultry, they can evolve to be highly pathogenic to poultry and sometimes to wild birds or humans. Thus, understanding how viruses move from wild birds into poultry is important. Aquatic birds such as ducks and geese are commonly infected with IAVs, but in many regions, these birds are uncommon on farms. Therefore, species that use both aquatic and agricultural areas may pose a risk by moving IAVs from aquatic birds to poultry. In this paper we evaluated whether European starlings, a species commonly found in both aquatic and agricultural habitats, can be infected by sharing water with IAV-infected ducks. We found that starlings can become infected when exposed to contaminated water, but IAV does not readily transmit between starlings. Consequently, starlings may pose a risk for spillover of IAVs to farms but are unlikely to maintain infections without exposure to other species.

Pregnancy is a valuable model to study the association between DNA methylation and several cardiometabolic traits, due to its direct potential to influence mother’s and child’s health. Epigenetics in Pregnancy (EPIPREG) is a population-based sample with the aim to study associations between DNA-methylation in pregnancy and cardiometabolic traits in South Asian and European pregnant women and their offspring. This cohort profile paper aims to present our sample with genetic and epigenetic data and invite researchers with similar cohorts to collaborative projects, such as replication of ours or their results and meta-analysis. In EPIPREG we have quantified epigenome-wide DNA methylation in maternal peripheral blood leukocytes in gestational week 28±1 in Europeans (n = 312) and South Asians (n = 168) that participated in the population-based cohort STORK Groruddalen, in Norway. DNA methylation was measured with Infinium MethylationEPIC BeadChip (850k sites), with technical validation of four CpG sites using bisulphite pyrosequencing in a subset (n = 30). The sample is well characterized with few missing data on e.g. genotype, universal screening for gestational diabetes, objectively measured physical activity, bioelectrical impedance, anthropometrics, biochemical measurements, and a biobank with maternal serum and plasma, urine, placenta tissue. In the offspring, we have repeated ultrasounds during pregnancy, cord blood, and anthropometrics up to 4 years of age. We have quantified DNA methylation in peripheral blood leukocytes in nearly all eligible women from the STORK Groruddalen study, to minimize the risk of selection bias. Genetic principal components distinctly separated Europeans and South Asian women, which fully corresponded with the self-reported ethnicity. Technical validation of 4 CpG sites from the methylation bead chip showed good agreement with bisulfite pyrosequencing. We plan to study associations between DNA methylation and cardiometabolic traits and outcomes.

Background Cardiorespiratory fitness (CRF) is the core element of health-related physical fitness evaluation. High pressure and low oxygen in Tibet (over 3,500 m above sea level) may negatively impact the residents’ CRF. The 20-m shuttle run test (20mSRT) is the most popular field-based assessment and estimate of CRF in children and adolescents worldwide. However, normative CRF data for the children and adolescents residing in China’s plateau region are unavailable, which prevents comparability among those living at high-altitudes around the world. Purpose To measure the CRF of Chinese children and adolescents aged 9–18 years living in Tibet at altitudes exceeding 3,500 m, and to identify correlations between this metric and demographic characteristics (age, sex, and ethnicity). These data were then compared with those generated in the lowland (Shanghai, China) and various global regions. Methods 20mSRT performance (number of completed laps) and predicted peak oxygen consumption (VO2peak) were used as indicators of CRF. We measured the CRF of 1,717 healthy children and adolescents aged 9–18 years living in Tibet. The CRF data from school-age subjects in Shanghai (2,437 boys and 2,396 girls) and worldwide (1,142,026 students from 50 countries/regions in Africa, Asia, Europe, Latin America, North America, and Oceania) were collated from published papers. Results The average CRF of the participants from Tibet was 39.8 mL/kg/min. The male subjects (n = 876; 41.1 ± 4.42 mL/kg/min) had a higher average CRF than their female counterparts (n = 841; 37.8 ± 5.40 mL/kg/min). CRF decreased with age in both sexes at statistical significance (F = 1249.9, p for trend 0.05). The indigenous Tibetans (n = 1289; 40.1 ± 3.71 mL/kg/min) had a significant higher average CRF than those of Han descent (n = 394; 38.9 ± 4.70 mL/kg/min) (p < 0.05). Conclusions Children and adolescents aged 7–18 years residing above 3,500 m in Tibet displayed lower CRF traits compared with their counterparts from the plains area and other high altitude places. CRF varied according to age, sex, and ethnic group. Given the importance of CRF in children and adolescents, effective intervention strategies should be implemented to improve CRF in children and adolescents on the plateau.