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Nepal has been strongly influenced by the COVID-19 pandemic and struggling to contain it with multiple interventions. We assessed the spatiotemporal dynamics of COVID-19 in the context of various restrictions imposed to contain the disease transmission by employing prospective spatiotemporal analysis with SaTScan statistics. We explored active and emerging disease clusters using the prospective space-time scanning with the Discrete Poisson model for two time periods using COVID-19 cases reported to the Ministry of Health and Population (MoHP), Government of Nepal during 23 January – 21 July, and 23 January – 29 November 2020 taking the cutoff date of 21 July (end date of nationwide lockdown). The results revealed that COVID-19 dynamics in the early transmission stage were slower and confined to a few districts. However, since the third week of April, transmission spread rapidly across the districts of Madhesh and Sudurpaschim Provinces. Despite nationwide lockdown, nine statistically significant active and emerging clusters were detected between 23 January and 21 July 2020, whereas seven emerging clusters were observed for an extended period to 29 November. After lifting the nationwide lockdown, COVID-19 clusters developed had a many-fold higher relative risk than during the lockdown period. The most likely cluster was located in the capital city, the Kathmandu valley, making it the highest-risk active cluster since August. Movement restriction appears to be the most effective non-pharmaceutical intervention against the COVID-19 in countries with limited health care facilities. Our findings could be valuable to the health authorities within Nepal and beyond to better allocate resources and improve interventions on the pandemic for containing it efficiently.

Background Visceral leishmaniasis (VL) is an important re-emerging neglected tropical disease associated with poverty. Despite the elimination initiative started in 2005, VL cases have been expanding into geographic areas in Nepal. The present study aims at exploring the trends of VL from 1980 to 2019. Methods This retrospective analysis covers 40 y of VL cases reported by the Epidemiology Diseases Control Division, Nepal. Subgroup analyses for annual incidence were performed by age, sex, seasons, districts and provinces, and VL cases were visualized on in-country maps. Results A total of 34 564 cases and 584 deaths of VL were reported during 1980–2019. VL persistently increased until 2006 and was reported from all seven provinces of the country. The highest number of confirmed cases (n=2229) was reported in 2003 and the lowest (n=60) in 1983. VL cases expanded from 12 to 23 endemic districts. The key components of the VL elimination program are early diagnosis; enhanced surveillance; integrated vector management; social mobilization; research and treatment. Conclusions Expansion of VL towards the hilly and mountain regions of Nepal has posed challenges to the elimination program. Urgent VL control measures are required to achieve the elimination goals.

Anemia among under-five children is the major health problem in Nepal. The lack of nutritional supplementation and lack of healthcare facilities are influential factors of anemia. Thus, the main objective of this study is to explore spatial variations and determinants of anemia among under-five children in Nepal. Nepal Demographic and Health Survey (NDHS) data from 2006 to 2016 were used in this study, which includes: household and individual-level data of 8555 under-five children, whose anemia was measured. In addition, a total of 260 (2006), 281 (2011), and 383 DHS clusters (2016) were taken in consideration for spatial analysis. The overall prevalence of anemia was 48.9%, 46.4%, and 52.2% in 2006, 2011, and 2016 respectively. The spatial analysis revealed a nonrandom spatial distribution, where statistically significant hotspots and coldspots were detected in different parts of the country. The results also identified mother’s age, mother’s educational level, socioeconomic status of household, number of under-5 children, household size, birth weight, underweight, stunting, diarrhea, and fever as associated factors of anemia among under-5 children. These findings may provide assistance to concerned health officials in adopting anemia-related programs and policies to address the anemia problems that plague Nepalese children under the age of five.

The coronavirus disease 19 (COVID-19), the biggest health problem at present, doesn’t have uniform transmission and severity among the countries and communities therein. Knowledge of community vulnerability to the disease would facilitate interventions aimed at transmission control by the efficient deployment of available limited resources. Therefore, we assessed spatial variations and heterogeneity of disease vulnerability among the population in 753 municipal units of Nepal. We collected geospatial indicators representing the domain of socioeconomic inequalities, population dynamics, heterogeneity in accessibility and the information related to underlying health condition which potentially affect the severity of COVID-19 transmission. Those indicators were assembled to create three vulnerability indices using Geographic Information System (GIS); Social Vulnerability Index (SVI), Epidemiological Vulnerability Index (EVI) and a composite of the two- Social and Epidemiological Vulnerability Index (SEVI). The indicators were scaled to a common measurement scale and spatially overlaid via equally weighted arithmetic mean. The indices were classified into five level of risk and the municipal units and the population within vulnerabilities classes were quantified and visualized in the map. The index output indicated high vulnerability to epidemics in megacities like Kathmandu, Pokhara, Bharatpur, etc.; developing cities especially in the Province No 2; and, municipal units of Karnali and Sudoorpashchim provinces. Additionally, some other municipalities such as Dhulikhel, Beshishahar, Tansen etc. which have a higher prevalence of pulmonary and cardiovascular disorders are highly vulnerable. The SVI indicated that 174 municipal units and 41.5% population is highly vulnerable. The EVI identified 55 municipal units and 40.7% of the total population of the country highly vulnerable to COVID-19. The SEVI accounted that disease vulnerability is high in 105 municipal units and 40% population of Nepal. The vulnerability indices created are means for different tiers of the existing government in federal system of Nepal for prioritization and improved planning for disease intervention especially in highly vulnerable municipal units where the COVID-19 transmission could have high severity.

Psychological problems increased during the period of COVID-19. Lockdown" is adopted in many countries of the world. It has also been seen that COVID-19 has led not only to an increase of infection and death but also vast change in the lifestyles of every individual especially in young adults causing various mental health issues. However, in Nepal, there are limited studies to address this issue. The main objective of this study is to generate evidence on the prevalence of symptoms of post-traumatic stress disorder, anxiety, and depression among young adults and the factors contributing to these outcomes in Nepal.Cross-sectional methods were employed using an online structured questionnaire in January 2021, among 1229 participants. Three logistic regression models were performed to examine the significant COVID-19 factors.The prevalence of Depression, Anxiety and post-traumatic stress disorder related symptoms in this study were 255(20.4%), 240(19.2%)and 162(13.2%) respectively relate.COVID-19 diagnosis, COVID-related stress and exposure was significantly related to depression. Similarly, COVID-19 diagnosis, change in income during COVID-19, being exposed to 4 or more exposure factors had high chances of getting anxiety. Also, income change during COVID-19 and stressors during COVID-19 were related to post-traumatic stress disorder.This research shows that various COVID-19 related factors have contributed to the high prevalence of these outcomes.

The World Health Organization sets up the Ambient Air Quality Guidelines mainly based on short-term and long-term health effects of air pollution. Previous studies, however, have generally revealed a non-threshold concentration-response relationship between air pollution and health, making it difficult to determine a concentration, below which no obvious health effects can be observed. Here we proposed a novel approach based on the concept of “number needed to treat”, specifically, we calculated the reduction in air pollution concentrations needed to avoid one death corresponding to different hypothetical concentration standards; the one with the smallest value would be the most practical concentration standard. As an example, we applied this approach to the daily standard of ambient PM2.5 (particulate matter with aerodynamic diameter ≤2.5 μm) in four Chinese cities. The calculation was based on the association between daily mortality and ambient PM2.5, which was examined by a generalized additive model with adjustment of important covariates. Significant associations were observed between PM2.5 and mortality. Our analyses suggested that it is appropriate to have 50 μg/m3 as the daily standard of ambient PM2.5 for the study area, compared to the current standard of which were directly adopted from the national standard of 75 μg/m3. This novel approach should be considered when planning and/or revising the ambient air quality guidelines/standards.

The novel coronavirus disease 2019 (COVID-19) has been the biggest public health problem of the present world. As the number of people suffering from the pandemic is rising, it is likely to claim more life and worsen the global health and economy. Nepal, one of the developing countries in the south Asia has been strongly influenced by the pandemic and struggling to contain it with multiple interventions, however, spatiotemporal dynamics of the epidemic and its linkage with various intervention strategies has not been studied yet. Here, we employed the prospective spatial-temporal analysis with SaTScan assessing dynamics of the COVID-19 cases from 23 January to 31 August 2020 at district level in Nepal. The results revealed that COVID-19 dynamics in the early stage of transmission was slower and confined in certain districts. However, from the third week of April, transmission spread rapidly across districts of Province No. 2 and Sudoorpaschim Province, primarily introduced by Nepalese citizens returning from India. Despite nationwide lockdown, nine statistically significant active and emerging clusters were detected between 23 January and 21 July 2020, whereas ten emerging clusters were observed for extended period to 31 August. The population density and population inflow from India crossing the sealed border had significant effects on the elevated risk of the epidemic. The capital city Kathmandu has become the highest-risk active cluster since August when travel restriction has been suspended. Movement restriction appears to be the most effective non-pharmaceutical intervention against the COVID-19 for resource-scarce countries with limited health care facilities. Our findings could be valuable to the health authorities within Nepal and beyond to better allocate resources and improve interventions on the pandemic for containing it efficiently.

Maternal blood glucose level is associated with fetal growth, therefore, its role in the associations between air pollution and birth weight deserves investigation. We examined the mediation effect of maternal blood glucose on the associations between maternal air pollution exposure and birth weight. A total of 10,904 pregnant women in Foshan, China during 2015–2019 were recruited. Oral glucose tolerance test (OGTT) was administered to each participant after late trimester 2. Air pollution data at the monitoring stations in residential districts was used to estimate exposures of each participant during trimester 1 and trimester 2. Mixed-effects linear models were used to estimate the associations between air pollution and birth weight. After controlling for ten covariates, the direct effect of PM2.5 and SO2 (each 10 μg/m3 increment) on birth weight was −15.7 g (95% CI: −29.4, −4.8 g) and −83.6 g (95% CI: −134.8, −33.0 g) during trimester 1. The indirect effect of PM2.5 and SO2 (each 10 μg/m3 increment) on birth weight by increasing maternal fasting glucose level was 6.6 g (95% CI: 4.6, 9.1 g) and 22.0 g (95% CI: 4.1, 44.0 g) during trimester 1. Our findings suggest that air pollution might affect the birth weight through direct and indirect pathway, and the indirect effect might be mediated by maternal blood glucose.

Being a globally emerging mite-borne zoonotic disease, scrub typhus is a serious public health concern in Nepal. Mapping environmental suitability and quantifying the human population under risk of the disease is important for prevention and control efforts. In this study, we model and map the environmental suitability of scrub typhus using the ecological niche approach, machine learning modeling techniques, and report locations of scrub typhus along with several climatic, topographic, Normalized Difference Vegetation Index (NDVI), and proximity explanatory variables and estimated population under the risk of disease at a national level. Both MaxEnt and RF technique results reveal robust predictive power with test The area under curve (AUC) and true skill statistics (TSS) of above 0.8 and 0.6, respectively. Spatial prediction reveals that environmentally suitable areas of scrub typhus are widely distributed across the country particularly in the low-land Tarai and less elevated river valleys. We found that areas close to agricultural land with gentle slopes have higher suitability of scrub typhus occurrence. Despite several speculations on the association between scrub typhus and proximity to earthquake epicenters, we did not find a significant role of proximity to earthquake epicenters in the distribution of scrub typhus in Nepal. About 43% of the population living in highly suitable areas for scrub typhus are at higher risk of infection, followed by 29% living in suitable areas of moderate-risk, and about 22% living in moderately suitable areas of lower risk. These findings could be useful in selecting priority areas for surveillance and control strategies effectively.

This study describes spatiotemporal distribution and geospatial diffusion patterns of dengue outbreak of 2013 in Jhapa district, Nepal. Laboratory-confirmed dengue cases were collected from the District Public Health Office, Government of Nepal. Choropleth mapping technique, Global Moran’s Index, SaTScan, and standard deviational ellipse were used to map and quantify the outbreak dynamics. The results revealed heterogeneous distribution and globally autocorrelated patterns. Local clusters were observed in 3 major urban centers. The standard deviational ellipse demonstrated the outbreak occurred from the east and diffused to the west along the east-west highway in different weeks. The results of this study could be useful to public health authorities to plan and execute dengue control strategies.

available on the PDFBanko Janakari Vol.12(1) 2002: 71-75

Background Most studies on the short-term health effects of air pollution have been conducted on a daily time scale, while hourly associations remain unclear. Methods We collected the hourly data of emergency ambulance calls (EACs), ambient air pollution, and meteorological variables from 2014 to 2016 in Luoyang, a central Chinese city in Henan Province. We used a generalized additive model to estimate the hourly effects of ambient air pollutants (PM2.5, PM10, SO2, and NO2) on EACs for all natural causes and cardiovascular and respiratory morbidity, with adjustment for potential confounding factors. We further examined the effect modification by temperature, relative humidity, wind speed, and atmospheric pressure using stratified analyses. Results In the single-pollutant models, PM2.5, PM10, SO2, and NO2 were associated with an immediate increase in all-cause morbidity at 0, 0, 12, 10 h, separately, after exposure to these pollutants (excess risks: 0.19% (95% confidence interval (CI): 0.03%, 0.35%), 0.13% (95% CI: 0.02%, 0.24%), 0.28% (95% CI: 0.01%, 0.54%) and 0.52% (95% CI: 0.06%, 0.99%), respectively). These effects remained generally stable in two-pollutant models. SO2 and NO2 were significantly associated with an immediate increase in risk of cardiovascular morbidity, but the effects on respiratory morbidity were relatively more delayed. The stratified analyses suggested that temperature could modify the association between PM2.5 and EACs, humidity and atmospheric pressure could modify the association between SO2 and EACs. Conclusions Our study provides new evidence that higher concentrations of PM2.5, PM10, SO2, and NO2 may have transiently acute effects on all-cause morbidity and subacute effects on respiratory morbidity. SO2 and NO2 may also have immediate effects on cardiovascular morbidity. Findings of this study have important implications for the formation of hourly air quality standards.

Background Ambient fine particulate matter pollution (PM2.5) is one leading cause of disease burden, but no study has quantified the association between daily PM2.5 exposure and life expectancy. We aimed to assess the potential benefits in life expectancy by attaining the daily PM2.5 standards in 72 cities of China during 2013–2016. Methods and findings We applied a two-stage approach for the analysis. At the first stage, we used a generalized additive model (GAM) with a Gaussian link to examine the city-specific short-term association between daily PM2.5 and years of life lost (YLL); at the second stage, a random-effects meta-analysis was used to generate the regional and national estimations. We further estimated the potential gains in life expectancy (PGLE) by assuming that ambient PM2.5 has met the Chinese National Ambient Air Quality Standard (NAAQS, 75 μg/m3) or the ambient air quality guideline (AQG) of the World Health Organization (WHO) (25 μg/m3). We also calculated the attributable fraction (AF), which denoted the proportion of YLL attributable to a higher-than-standards daily mean PM2.5 concentration. During the period from January 18, 2013 to December 31, 2016, we recorded 1,226,849 nonaccidental deaths in the study area. We observed significant associations between daily PM2.5 and YLL: each 10 μg/m3 increase in three-day–averaged (lag02) PM2.5 concentrations corresponded to an increment of 0.43 years of life lost (95% CI: 0.29–0.57). We estimated that 168,065.18 (95% CI: 114,144.91–221,985.45) and 68,684.95 (95% CI: 46,648.79–90,721.11) years of life lost can be avoided by achieving WHO’s AQG and Chinese NAAQS in the study area, which corresponded to 0.14 (95% CI: 0.09–0.18) and 0.06 (95% CI: 0.04–0.07) years of gain in life expectancy for each death in these cities. We observed differential regional estimates across the 7 regions, with the highest gains in the Northwest region (0.28 years of gain [95% CI: 0.06–0.49]) and the lowest in the North region (0.08 [95% CI: 0.02–0.15]). Furthermore, using WHO’s AQG and Chinese NAAQS as the references, we estimated that 1.00% (95% CI: 0.68%–1.32%) and 0.41% (95% CI: 0.28%–0.54%) of YLL could be attributable to the PM2.5 exposure at the national level. Findings from this study were mainly limited by the unavailability of data on individual PM2.5 exposure. Conclusions This study indicates that significantly longer life expectancy could be achieved by a reduction in the ambient PM2.5 concentrations. It also highlights the need to formulate a stricter ambient PM2.5 standard at both national and regional levels of China to protect the population’s health., Jinlei Qi and colleagues reveal the potential gains in life expectancy in China by reducing ambient PM2.5 concentrations., Author summary Why was this study done? Ambient fine particulate matter (PM2.5) pollution is a severe environmental health concern in China. Both short-term and long-term exposure to PM2.5 have been found to be associated with increased mortality and years of life lost. A few studies have estimated the association between annual PM2.5 concentration and life expectancy, but there is no report on the effects of daily PM2.5 exposure on life expectancy. What did the researchers do and find? This nationwide time-series study collected data on more than 1 million nonaccidental deaths in 72 Chinese cities from January 18, 2013 to December 31, 2016. We used a generalized additive model to explore the city-specific association between daily PM2.5 and years of life lost and then conducted random-effects meta-analyses to generate the regional and national estimates. During the study period from January 18, 2013 to December 31, 2016, we estimated that 168,065.18 (about 1.00% of the total) years of life lost can be avoided by achieving WHO’s guideline on daily PM2.5 concentrations (25 μg/m3) in the study area, which corresponded to 0.14 years of gains in life expectancy for each death. What do these findings mean? This is the first study to report the potential gains in life expectancy by attaining the daily standards of PM2.5, which provided important and useful information of the burden caused by ambient PM2.5 pollution. In the future, there should be a policy of stricter ambient PM2.5 standards at both national and regional levels in China, which would benefit the population’s health and life expectancy.

Although myopia has been largely ignored among the elderly population, there is an increased risk of myopia with advancing age. Ambient air pollution is one potential contributor to vision impairments, but few epidemiological studies have demonstrated such an association. This cross-sectional survey collected the information of 33,626 subjects aged ≥50 years in six developing countries during 2007–2010. Myopia was identified based on questions related to symptoms of myopia. The annual concentrations of fine particulate matter (PM2.5) and ozone (O3) were estimated with the satellite data and chemical transport model. We examined the associations between the two pollutants and myopia using mixed-effect Poisson regression models with robust variance estimation (sandwich estimation). We observed J-shaped associations between the two pollutants and myopia, and identified 12 and 54 μg/m3 as the threshold concentrations. The adjusted prevalence ratio was 1.12 (95% CI: 1.05, 1.21) and 1.26 (95% CI: 1.14, 1.38) for each standard deviation (SD) increase in PM2.5 and O3 concentrations above their threshold, respectively. In addition, the interaction analysis suggested a synergistic interaction of these two pollutants on myopia in the additive model, with a synergistic index of 1.81 (Bootstrapping 95% CI: 0.92, 4.94). Our results indicate that long-term exposures to PM2.5 and O3 might be important environmental risk factors of myopia in the elderly, and suggest that more efforts should be taken to reduce airborne PM2.5 and O3 levels to protect vision health.

Background To investigate the effects of air pollution exposure during pregnancy on the indicators of glucose homeostasis and gestational diabetes mellitus (GDM). Methods We conducted a birth cohort study in Foshan, China during 2015–2019. Oral glucose tolerance test (OGTT) was administered to each participant during pregnancy. GDM was defined according to the International Association of Diabetes and Pregnancy Study Groups criteria (IADPSG). Air pollutant (fine particulate matter (PM2.5), particulate matter with an aerodynamic diameter of 10 μm or less (PM10), sulfate dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3)) concentrations from the air monitoring stations in Foshan were used to estimate individual air pollutant exposure during the first two trimesters. Linear and logistic regression models were employed to estimate the associations between air pollution exposure during the first two trimesters and OGTT glucose levels and GDM. Results Of 12,842 pregnant women, 3055 (23.8%) had GDM. A 10 μg/m3 increase in PM2.5, PM10 and SO2 during trimester 1, trimester 2 and two trimesters were associated with 0.07 mmol/L to 0.29 mmol/L increment in OGTT-fasting glucose levels in single-pollutant model. A 10 μg/m3 increase in NO2 and O3 during two trimesters were associated with 0.15 mmol/L and 0.12 mmol/L decrease in OGTT-fasting glucose in single-pollutant model. However, no significant or weaker effects of O3 during two trimesters on OGTT-fasting glucose were observed in two-pollutant models. Moreover, exposure to PM2.5, PM10 and SO2 were associated with increased risk of GDM in both single- and two-pollutant models. Conclusions Our study suggests PM2.5, PM10 and SO2 exposure during the first two trimesters might increase the risk of GDM.

Background Previous research has reported the effects of long-term fine particulate matter (PM2.5) pollution on years of life lost (YLL), but these effects may not represent the full impact. This study aims to estimate potential benefits in life time from adhering to daily ambient PM2.5 concentration standards/guidelines. Methods This study evaluated the relationship between daily ambient PM2.5 level and YLL using a two-stage approach with generalized additive models and meta-analysis. Potential life expectancy gains were then estimated by presuming that daily PM2.5 levels were in compliance with the Chinese and WHO standards. In addition, the attributable fraction of YLL due to excess PM2.5 exposure was also calculated. Results During 2013–2016, 459,468 non-accidental deaths were recorded in the six cities of Pearl River Delta, China. Each 10 μg/m3 increment in four-day average (lag03) level of PM2.5 was related to an increment of 13.31 [95% confidence interval (CI): 5.74, 20.87] years of life lost. Implementation of the WHO guidelines might avoid 180,980.83 YLLs (95% CI: 78,116.07, 283,845.60), which corresponded to 0.39 (95% CI: 0.17, 0.62) years of increased life time per death. Additionally, an estimated 0.15% (95% CI: 0.06%, 0.23%) or 2.04% (95% CI: 0.88%, 3.20%) of YLLs could be attributed to PM2.5 exposures higher than the Chinese or WHO guidelines, respectively. Conclusions This study suggests that people might live longer by controlling daily PM2.5 concentration and highlights the need to adopt stricter standards in China.

Objectives Prenatal exposure to air pollutant has been associated with congenital heart defect (CHD). However, no study has investigated this effect in pre-pregnancy overweighted women. This study aimed to evaluate gestational exposure to particulate pollutant (PM2.5) and gaseous air pollutants (O3 and NO2) on the risk of CHD, and explore the potential effect modifiers including maternal age, pre-pregnancy BMI and pregestational diseases. Methods In this birth cohort study, a total of 63,213 pregnant women in Foshan, China were initially recruited and followed from their first hospital visit for pregnancy to delivery during 2015–2019. CHD cases were confirmed by the records in hospital- and population- based birth defect surveillance systems. Air pollutant exposures were estimated by the daily concentrations measured in air monitoring stations in each participant's residential county. Mixed-effects regression models, adjusted for potential confounding factors were applied to estimate the associations between air pollutant and CHD during the first three months of the pregnancy. Results A total of 985 (1.6%) newborns were identified as CHD cases. For each 10 μg/m3 increase in ambient O3 during the 1st month, the OR values for CHD were 1.03 (95% CI: 0.94, 1.13) in pre-pregnancy normal weighted women and 1.24 (95% CI: 1.01, 1.53) in pre-pregnancy overweighted women. For each 10 μg/m3 increase in NO2 during the 3rd month, the OR values for CHD were 1.09 (95% CI: 1.01, 1.18) in pre-pregnancy normal weighted women and 1.27 (95% CI: 1.07, 1.51) in pre-pregnancy overweighted women. No significant associations were found between PM2.5 exposure and CHD in our analysis. Conclusions This study demonstrates that gaseous air pollutants (O3 and NO2) exposure during the cardiac embryogenesis period is associated with an increased risk of CHD, particularly for pre-pregnancy overweighted women.

Anthropogenic activities have driven many wildlife species towards extinction. Among these species, the geographic distributions of many are poorly documented, which can limit the effectiveness of conservation. The critically endangered Chinese pangolin (Manis pentadactyla) is experiencing population decline throughout its range due to land-use changes and illegal trade for food and traditional medicine. Using distribution records and maximum entropy modeling, we predicted the potential distribution of the Chinese pangolin across Nepal. Most suitable potential habitats of the Chinese pangolin occurred in forest areas of the mid-hill region in central and eastern Nepal, followed by cultivated land. Almost all potential suitable habitats of the Chinese pangolin occurred outside of protected areas, and most of them were encroached upon by cultivated land, human settlements, and infrastructure developments. The results from this study provide baseline information on the potential suitable habitats of the Chinese pangolin in Nepal, which helps to develop site- and species-specific management plans and to identify priority areas to minimize the current threats to the pangolin and enhance the stewardship of species conservation.

Urban growth is a key indicator of economic development. At the same time, haphazard urban growth creates serious socioeconomic, environmental and urban land management problems. In this context, understanding the process of urban landscape change is important for guiding the sustainable growth of urban areas. This study analyzes the urban land changes during 1990–2018 in two metropolitan cities of Gandaki basin: Pokhara and Bharatpur. Landsat satellite images were analyzed using supervised classification methods. The results revealed that the built-up area has increased significantly by 300% in Pokhara and by nearly 500% in the Bharatpur during the past 28 years. Population growth, migration from surrounding areas due to urban facilities and the easy lifestyle in cities were found to be major determinants of urban growth within the study area. In addition, the changing urban definition and expansion of municipal boundaries are key factors for rapid urban growth. Both cities are likely to grow in the future as they are both located in areas that encompass the high levels of commercial activity and modern service facilities. The haphazard urban growth should be minimized through planning and policies for sustainable urban development.

City green infrastructure (CGI) makes cities more resilient and sustainable, as required by the United Nations’ (UN) Sustainable Development Goal 11–Sustainable Cities and Communities. Based on the CGI policies of Beijing, land use/land cover (LULC) changes of two Asian capitals, Beijing, China and Islamabad, Pakistan, are simulated. LULC maps for 2010 and 2015 are developed by applying object-based image analysis (OBIA) to Landsat imagery. Dynamics of land system (DLS) model was used to simulate the LULC changes for 2020 and 2025 under three scenarios: (1) business-as-usual (BAU); (2) urban green space work plan (UGWP); and (3) landscape and greening policies (LGP). Results reveal that DLS is efficient than other simulation models. The BAU scenario predicts an overall expansion in Beijing’s greenery, while Islamabad will encounter a decline by 7.3 km2 per year. Under the UGWP scenario, urban green spaces and other vegetation area of Beijing will expand by 7.6 km2, while, for Islamabad, vegetation degradation rate will slow down to 6.9 km2 per year. The LGP scenario envisage a massive increase of 23.5 km2 per year in green resources of Beijing and Islamabad’s green land loss rate will further slowdown to 6.1 km2 per year. It is inferred from the results that vegetation degradation in Islamabad need to lessen by implementing LGP policy after basic amendments according to the local conditions and available resources.

Increasing trends of urbanization lead to vegetation degradation in big cities and affect the urban thermal environment. This study investigated (1) the cooling effect of urban green space spatial patterns on Land Surface Temperature (LST); (2) how the surrounding environment influences the green space cool islands (GCI), and vice versa. The study was conducted in two Asian capitals: Beijing, China and Islamabad, Pakistan by utilizing Gaofen-1 (GF-1) and Landsat-8 satellite imagery. Pearson’s correlation and normalized mutual information (NMI) were applied to investigate the relationship between green space characteristics and LST. Landscape metrics of green spaces including Percentage of Landscape (PLAND), Patch Density (PD), Edge Density (ED), and Landscape Shape Index (LSI) were selected to calculate the spatial patterns of green spaces, whereas GCI indicators were defined by Green Space Range (GR), Temperature Difference (TD), and Temperature Gradient (TG). The results indicate that both vegetation composition and configuration influence LST distributions; however, vegetation composition appeared to have a slightly greater effect. The cooling effect can be produced more effectively by increasing green space percentage, planting trees in large patches with equal distribution, and avoiding complex-shaped green spaces. The GCI principle indicates that LST can be decreased by increasing the green space area, increasing the water body fraction, or by decreasing the fraction of impervious surfaces. GCI can also be strengthened by decreasing the fraction of impervious surfaces and increasing the fraction of water body or vegetation in the surrounding environment. The cooling effect of vegetation and water could be explained based on their thermal properties. Beijing has already enacted the green-wedge initiative to increase the vegetation canopy. While designing the future urban layout of Islamabad, the construction of artificial lakes within the urban green spaces would also be beneficial, as is the case with Beijing.

Supplemental material, Supplementary_file_Editorial_Office for Spatiotemporal Distribution and Geospatial Diffusion Patterns of 2013 Dengue Outbreak in Jhapa District, Nepal by Bipin Kumar Acharya, Chunxiang Cao, Min Xu, Wei Chen, Shreejana Pandit in Asia Pacific Journal of Public Health

Both the number of cases of dengue fever and the areas of outbreaks within Nepal have increased significantly in recent years. Further expansion and range shift is expected in the future due to global climate change and other associated factors. However, due to limited spatially-explicit research in Nepal, there is poor understanding about the present spatial distribution patterns of dengue risk areas and the potential range shift due to future climate change. In this context, it is crucial to assess and map dengue fever risk areas in Nepal. Here, we used reported dengue cases and a set of bioclimatic variables on the MaxEnt ecological niche modeling approach to model the climatic niche and map present and future (2050s and 2070s) climatically suitable areas under different representative concentration pathways (RCP2.6, RCP6.0 and RCP8.5). Simulation-based estimates suggest that climatically suitable areas for dengue fever are presently distributed throughout the lowland Tarai from east to west and in river valleys at lower elevations. Under the different climate change scenarios, these areas will be slightly shifted towards higher elevation with varied magnitude and spatial patterns. Population exposed to climatically suitable areas of dengue fever in Nepal is anticipated to further increase in both 2050s and 2070s on all the assumed emission scenarios. These findings could be instrumental to plan and execute the strategic interventions for controlling dengue fever in Nepal.

Dengue fever is expanding rapidly in many tropical and subtropical countries since the last few decades. However, due to limited research, little is known about the spatial patterns and associated risk factors on a local scale particularly in the newly emerged areas. In this study, we explored spatial patterns and evaluated associated potential environmental and socioeconomic risk factors in the distribution of dengue fever incidence in Jhapa district, Nepal. Global and local Moran's I were used to assess global and local clustering patterns of the disease. The ordinary least square (OLS), geographically weighted regression (GWR), and semi-parametric geographically weighted regression (s-GWR) models were compared to describe spatial relationship of potential environmental and socioeconomic risk factors with dengue incidence. Our result revealed heterogeneous and highly clustered distribution of dengue incidence in Jhapa district during the study period. The s-GWR model best explained the spatial association of potential risk factors with dengue incidence and was used to produce the predictive map. The statistical relationship between dengue incidence and proportion of urban area, proximity to road, and population density varied significantly among the wards while the associations of land surface temperature (LST) and normalized difference vegetation index (NDVI) remained constant spatially showing importance of mixed geographical modeling approach (s-GWR) in the spatial distribution of dengue fever. This finding could be used in the formulation and execution of evidence-based dengue control and management program to allocate scare resources locally.

Although ambient air pollution has been consistently associated with morbidity and mortality of stroke, there is limited evidence on whether the control of air pollution would associate with a reduced risk of stroke. The citywide air pollution controlling measures during the 2010 Asian Games in Guangzhou provided such an opportunity to answer this question. We collected daily data on the concentrations of air pollutants and mortality from ischemic and hemorrhagic stroke, and compared them for 51 intervention days in 2010 with the corresponding days in 2006–2009 and 2011 (reference period). Poisson-based interrupted time series analysis was employed to estimate the relative risk (RR) and 95% confidence interval (CI). The daily mean concentrations of PM10 (particles with an aerodynamic diameter smaller than 10 μm) was 88.64 μg/m3 during the reference period, and 80.47 μg/m3 during the intervention period. Daily mortality number of total stroke, ischemic and hemorrhagic stroke decreased from 3.67, 2.00 and 1.67 during the reference period, to 3.00, 1.76 and 1.24 during the intervention period; the corresponding RR was 0.79 (95% CI: 0.66–0.94), 0.87 (95% CI: 0.69–1.11) and 0.69 (95% CI: 0.52–0.91), respectively. Our findings show that ambient air pollution controlling measures during the 2010 Asian Games in Guangzhou were associated with a decreased risk of stroke mortality, which suggests a need to reduce air pollution to improve public health.

Background Due to recent emergence, dengue is becoming one of the major public health problems in Nepal. The numbers of reported dengue cases in general and the area with reported dengue cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of dengue have not been investigated yet. This study aims to fill this gap by analyzing spatiotemporal patterns based on monthly surveillance data aggregated at district. Methods Dengue cases from 2010 to 2014 at district level were collected from the Nepal government’s health and mapping agencies respectively. GeoDa software was used to map crude incidence, excess hazard and spatially smoothed incidence. Cluster analysis was performed in SaTScan software to explore spatiotemporal clusters of dengue during the above-mentioned time period. Results Spatiotemporal distribution of dengue fever in Nepal from 2010 to 2014 was mapped at district level in terms of crude incidence, excess risk and spatially smoothed incidence. Results show that the distribution of dengue fever was not random but clustered in space and time. Chitwan district was identified as the most likely cluster and Jhapa district was the first secondary cluster in both spatial and spatiotemporal scan. July to September of 2010 was identified as a significant temporal cluster. Conclusion This study assessed and mapped for the first time the spatiotemporal pattern of dengue fever in Nepal. Two districts namely Chitwan and Jhapa were found highly affected by dengue fever. The current study also demonstrated the importance of geospatial approach in epidemiological research. The initial result on dengue patterns and risk of this study may assist institutions and policy makers to develop better preventive strategies.

Land use and land cover is a fundamental variable that affects many parts of social and physical environmental aspects. Land use and land cover changes (LUCC) has been known as one of the key drivers of affecting in ecosystem services. The trans-boundary Gandaki River Basin (GRB) is the part of Central Himalayas, a tributary of Ganges mega-river basin plays a crucial role on LUCC and ecosystem services. Due to the large topographic variances, the basin has existed various land cover types including cropland, forest cover, built-up area, river/lake, wetland, snow/glacier, grassland, barren land and bush/shrub. This study used Landsat 5-TM (1990), Landsat 8-OLI (2015) satellite image and existing national land cover database of Nepal of the year 1990 to analyze LUCC and impact on ecosystem service values between 1990 and 2015. Supervised classification with maximum likelihood algorithm was applied to obtain the various land cover types. To estimate the ecosystem services values, this study used coefficients values of ecosystem services delivered by each land cover class. The combined use of GIS and remote sensing analysis has revealed that grassland and snow cover decreased from 10.62% to 7.62% and 9.55% to 7.27%, respectively compared to other land cover types during the 25 years study period. Conversely, cropland, forest and built-up area have increased from 31.78% to 32.67%, 32.47&ndash, 33.22% and 0.19&ndash, 0.59%, respectively in the same period. The total ecosystem service values (ESV) was increased from 50.16 &times, 108 USD y&minus, 1 to 51.84 &times, 1 during the 25 years in the GRB. In terms of ESV of each of land cover types, the ESV of cropland, forest, water bodies, barren land were increased, whereas, the ESV of snow/glacier and grassland were decreased. The total ESV of grassland and snow/glacier cover were decreased from 3.12 &times, 1 to 1.93 &times, 1 and 0.26 &times, 1 to 0.19 &times, 1, respectively between 1990 and 2015. The findings of the study could be a scientific reference for the watershed management and policy formulation to the trans-boundary watershed.

Genetic diversity of a species is influenced by multiple factors, including the Quaternary glacial-interglacial cycles and geophysical barriers. Such factors are not yet well documented for fauna from the southern border of the Himalayan region. This study used mitochondrial DNA (mtDNA) sequences and ecological niche modeling (ENM) to explore how the late Pleistocene climatic fluctuations and complex geography of the Himalayan region have shaped genetic diversity, population genetic structure, and demographic history of the Nepalese population of Assam macaques (Macaca assamensis) in the Himalayan foothills. A total of 277 fecal samples were collected from 39 wild troops over almost the entire distribution of the species in Nepal. The mtDNA fragment encompassing the complete control region (1121 bp) was recovered from 208 samples, thus defining 54 haplotypes. Results showed low nucleotide diversity (0.0075 ± SD 0.0001) but high haplotype diversity (0.965 ± SD 0.004). The mtDNA sequences revealed a shallow population genetic structure with a moderate but statistically significant effect of isolation by distance. Demographic history analyses using mtDNA sequences suggested a post-pleistocene population expansion. Paleodistribution reconstruction projected that the potential habitat of the Assam macaque was confined to the lower elevations of central Nepal during the Last Glacial Maximum. With the onset of the Holocene climatic optimum, the glacial refugia population experienced eastward range expansion to higher elevations. We conclude that the low genetic diversity and shallow population genetic structure of the Assam macaque population in the Nepal Himalaya region are the consequence of recent demographic and spatial expansion.

The rapid increase in urbanization due to population growth leads to the degradation of vegetation in major cities. This study investigated the spatial patterns of the ecoenvironmental conditions of inhabitants of two distinct Asian capital cities, Beijing of China and Islamabad of Pakistan, by utilizing Earth observation data products. The significance of urban vegetation for the cooling effect was studied in local climate zones, i.e., urban, suburban, and rural areas within 1-km2 quantiles. Landsat-8 (OLI) and Gaofen-1 satellite imagery were used to assess vegetation cover and land surface temperature, while population datasets were used to evaluate environmental impact. Comparatively, a higher cooling effect of vegetation presence was observed in rural and suburban zones of Beijing as compared to Islamabad, while the urban zone of Islamabad was found comparatively cooler than Beijing’s urban zone. The urban thermal field variance index calculated from satellite imagery was ranked into the ecological evaluation index. The worst ecoenvironmental conditions were found in urban zones of both cities where the fraction of vegetation is very low. Meanwhile, this condition is more serious in Beijing, as more than 90% of the total population is living under the worst ecoenvironment conditions, while only 7% of the population is enjoying comfortable conditions. Ecoenvironmental conditions of Islamabad are comparatively better than Beijing where ∼61% of the total population live under the worst ecoenvironmental conditions, and ∼24% are living under good conditions. Thus, Islamabad at this early growth stage can learn from Beijing’s ecoenvironmental conditions to improve the quality of living by controlling the associated factors in the future.

The Community Forestry has been the most effective means of managing common forest resources in Nepal. Besides rehabilitating degraded hills, improving environment and contributing to the rural livelihoods, community forestry is claimed to be a major means of biodiversity conservation. It is also argued that the prevalent approach of community forest management threats to the conservation of biodiversity. This paper is based on the findings from two community forest user groups from Central Nepal and argues that the users’ innovative practices of active forest management favor biodiversity conservation. The study has documented users’ innovations to conserve biodiversity in community managed forests. Key words: Nepal, community forestry, biodiversity conservation and livelihoods Banko Janakari Vol.16(1) 2006 pp46-56