Spatio-temporal patterns of childhood pneumonia in Bhutan: a Bayesian analysis

AbstractPneumonia is one of the top 10 diseases by morbidity in Bhutan. This study aimed to investigate the spatial and temporal trends and risk factors of childhood pneumonia in Bhutan. A multivariable Zero-inflated Poisson regression model using a Bayesian Markov chain Monte Carlo simulation was undertaken to quantify associations of age, sex, altitude, rainfall, maximum temperature and relative humidity with monthly pneumonia incidence and to identify the underlying spatial structure of the data. Overall childhood pneumonia incidence was 143.57 and 10.01 per 1000 persons over 108 months of observation in children aged < 5 years and 5–14 years, respectively. Children < 5 years or male sex were more likely to develop pneumonia than those 5–14 years and females. Each 1 °C increase in maximum temperature was associated with a 1.3% (95% (credible interval [CrI] 1.27%, 1.4%) increase in pneumonia cases. Each 10% increase in relative humidity was associated with a 1.2% (95% CrI 1.1%, 1.4%) reduction in the incidence of pneumonia. Pneumonia decreased by 0.3% (CrI 0.26%, 0.34%) every month. There was no statistical spatial clustering after accounting for the covariates. Seasonality and spatial heterogeneity can partly be explained by the association of pneumonia risk to climatic factors including maximum temperature and relative humidity.

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Spatio-temporal patterns of pneumonia in Bhutan: A Bayesian analysis

10.21203/rs.3.rs-152074/v1 ◽

2021 ◽

Author(s):

Kinley Wangdi ◽

Kinley Penjor ◽

Tsheten Tsheten ◽

Chachu Tshering ◽

Peter Gething ◽

...

Keyword(s):

Risk Factors ◽

Relative Humidity ◽

Poisson Regression ◽

Spatial Clustering ◽

Climatic Factors ◽

Temporal Trends ◽

Credible Interval ◽

Maximum Temperature ◽

Spatio Temporal ◽

Spatial And Temporal Trends

Abstract Pneumonia is one of the top 10 diseases by morbity in Bhutan. This study aimed to investigate the spatial and temporal trends and risk factors of pneumonia in Bhutan. A multivariable Zero-inflated Poisson regression using a Bayesian Markov chain Monte Carlo simulation was undertaken to quantify associations of age, sex, rainfall, maximum temperature and relative humidity with monthly pneumonia incidence and identify underlying spatial structure of the data. Overall pneumonia incidence was 96.5 and 4.57 per 1,000 populations over nine years in people aged < 5 years and ≥ 5 years, respectively. Children < 5 years or being a female are more like to get pneumonia than ≥ 5 years and males. A 10mm increase in rainfall and 1°C increase in maximum temperature was associated with a 7.2% (95% (credible interval [CrI] 0.7%, 14.0%) and 28.6% (95% CrI 27.2%, 30.1%) increase in pneumonia cases. A 1% increase in relative humidity was associated with a decrease in the incidence of pneumonia by 8.6% (95% CrI 7.5%, 9.7%). There was no evidence of spatial clustering after accounting for the covariates. Seasonality and spatial heterogeneity can partly be explained by the association of pneumonia risk to climatic factors including rainfall, maximum temperature and relative humidity.

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Spatiotemporal transmission and socio-climatic factors related to paediatric tuberculosis in north-western Ethiopia

Geospatial health ◽

10.4081/gh.2017.575 ◽

2017 ◽

Author(s):

Kefyalew Addis Alene ◽

Kerri Viney ◽

Emma S. McBryde ◽

Archie C.A. Clements

Keyword(s):

Spatial Clustering ◽

Climatic Factors ◽

Credible Interval ◽

Educational Status ◽

Northwest Ethiopia ◽

Incidence Rates ◽

Childhood Tb ◽

Spatio Temporal ◽

North Western ◽

Western Ethiopia

The burden of tuberculosis (TB) in children reflects continuing and recent transmission within a population. This study aimed to identify spatiotemporal and socio-climatic factors associated with paediatric TB in north-western Ethiopia. Multivariate Poisson regression models were computed using a Bayesian framework. Estimates of parameters were generated using Markov chain Monte Carlo simulation. A total of 2,240 children aged under 15 years diagnosed with TB during the years 2013- 2016 were included in the analysis. The annual TB incidence rates were 44 and 28 per 100,000 children, for children aged under 15 and 5 years, respectively. Spatial clustering of TB was observed in the border area of north-western Ethiopia. The spatio-temporal transmission of childhood TB was found to be associated with district level socio-climatic factors such as urbanisation [relative risk (RR): 1.8; 95% credible interval (CrI): 1.2, 2.6], lower educational status (RR: 1.5; 95% CrI: 1.0, 2.1), a high percentage of internal migration (RR: 1.3; 95% CrI: 1.0, 1.6), high temperature (RR: 1.3; 95% CrI: 1.0, 1.7) and high rainfall (RR: 1.5; 95% CrI: 1.1, 2.0). We conclude that interventions targeting hotspot districts with a high proportion of childhood TB are important to reduce TB transmission in northwest Ethiopia.

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Influence of Climatic Factors on Malaria Epidemic in Gulu District, Northern Uganda: A 10-Year Retrospective Study

Malaria Research and Treatment ◽

10.1155/2018/5482136 ◽

2018 ◽

Vol 2018 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Ouma Simple ◽

Arnold Mindra ◽

Gerald Obai ◽

Emilio Ovuga ◽

Emmanuel Igwaro Odongo-Aginya

Keyword(s):

Retrospective Study ◽

Relative Humidity ◽

Malaria Control ◽

Malaria Infection ◽

Climatic Factors ◽

Indoor Residual Spraying ◽

Sub Saharan Africa ◽

Maximum Temperature ◽

Northern Uganda ◽

Gulu District

Background. Globally, 15 countries, mainly in Sub-Saharan Africa, account for 80% of malaria cases and 78% of malaria related deaths. In Uganda, malaria is endemic and the mortality and morbidity due to malaria cause significant negative impact on the economy. In Gulu district, malaria is the leading killer disease among children <5 years. In 2015, the high intensity of malaria infection in Northern Uganda revealed a possible link between malaria and rainfall. However, available information on the influence of climatic factors on malaria are scarce, conflicting, and highly contextualized and therefore one cannot reference such information to malaria control policy in Northern Uganda, thus the need for this study. Methods and Results. During the 10 year’s retrospective study period a total of 2,304,537 people suffered from malaria in Gulu district. Malaria infection was generally stable with biannual peaks during the months of June-July and September-October but showed a declining trend after introduction of indoor residual spraying. Analysis of the departure of mean monthly malaria cases from the long-term mean monthly malaria cases revealed biannual seasonal outbreaks before and during the first year of introduction of indoor residual spraying. However, there were two major malaria epidemics in 2015 following discontinuation of indoor residual spraying in the late 2014. Children <5 years of age were disproportionally affected by malaria and accounted for 47.6% of the total malaria cases. Both rainfall (P=0.04) and relative humidity (P=0.003) had significant positive correlations with malaria. Meanwhile, maximum temperature had significant negative correlation with malaria (P=0.02) but minimum temperature had no correlation with malaria (P=0.29). Conclusion. Malaria in Gulu disproportionately affects children under 5 years and shows seasonality with a generally stable trend influenced by rainfall and relative humidity. However, indoor residual spraying is a very promising method to achieve a sustained malaria control in this population.

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Forecasting Malaria Cases Using Climatic Factors in Delhi, India: A Time Series Analysis

Malaria Research and Treatment ◽

10.1155/2014/482851 ◽

2014 ◽

Vol 2014 ◽

pp. 1-6 ◽

Cited By ~ 14

Author(s):

Varun Kumar ◽

Abha Mangal ◽

Sanjeet Panesar ◽

Geeta Yadav ◽

Richa Talwar ◽

...

Keyword(s):

Time Series ◽

Relative Humidity ◽

Time Series Analysis ◽

Time Series Data ◽

Climatic Factors ◽

Series Data ◽

Maximum Temperature ◽

Climatic Data ◽

Training Centre ◽

Series Analysis

Background. Malaria still remains a public health problem in developing countries and changing environmental and climatic factors pose the biggest challenge in fighting against the scourge of malaria. Therefore, the study was designed to forecast malaria cases using climatic factors as predictors in Delhi, India. Methods. The total number of monthly cases of malaria slide positives occurring from January 2006 to December 2013 was taken from the register maintained at the malaria clinic at Rural Health Training Centre (RHTC), Najafgarh, Delhi. Climatic data of monthly mean rainfall, relative humidity, and mean maximum temperature were taken from Regional Meteorological Centre, Delhi. Expert modeler of SPSS ver. 21 was used for analyzing the time series data. Results. Autoregressive integrated moving average, ARIMA (0,1,1) (0,1,0)12, was the best fit model and it could explain 72.5% variability in the time series data. Rainfall (P value = 0.004) and relative humidity (P value = 0.001) were found to be significant predictors for malaria transmission in the study area. Seasonal adjusted factor (SAF) for malaria cases shows peak during the months of August and September. Conclusion. ARIMA models of time series analysis is a simple and reliable tool for producing reliable forecasts for malaria in Delhi, India.

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Spatio-Temporal Variation of Reference Evapotranspiration and Its Climatic Drivers over the Tibetan Plateau during 1970–2018

Applied Sciences ◽

10.3390/app11178013 ◽

2021 ◽

Vol 11 (17) ◽

pp. 8013

Author(s):

Shanshan Hu ◽

Ruyi Gao ◽

Tao Zhang ◽

Peng Bai ◽

Rui Zhang

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Tibetan Plateau ◽

Reference Evapotranspiration ◽

Climatic Factors ◽

Kendall Test ◽

The Tibetan Plateau ◽

Variation Characteristics ◽

Climatic Drivers ◽

Spatio Temporal

Reference evapotranspiration (ET0) is a key component of hydrologic cycle and it is important for water resources management. Analysis of ET0 changes is particularly critical for understanding the impacts of climatic change on hydrology in ecologically fragile regions. In this study, using the Penman–Monteith method and the Mann–Kendall test, the variation characteristics of ET0 on the Tibetan Plateau (TP) from 1970 to 2018 was analyzed, and the dominant climatic factors controlling the change of ET0 was also explored. The result shows that in TP region: (1) there was an abrupt change in the trend of ET0 around 1997, and the ET0 declined at a rate of −25.9 mm/decade during 1970–1996 but increased by 31.1 mm/decade during 1997–2018; (2) ET0 is most sensitive to solar radiation, then relative humidity, wind speed and mean temperature; (3) the decrease of ET0 before 1997 was mainly due to the decline of wind speed and the increase of relative humidity, while the increase of ET0 after 1997 was mainly due to the decrease of relative humidity. The results of this study can provide data reference for the research of water balance on the TP.

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Spatio-Temporal Trends of Fire in Slash and Burn Agriculture Landscape: A Case Study from Nagaland, India

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-ii-8-53-2014 ◽

2014 ◽

Vol II-8 ◽

pp. 53-59 ◽

Cited By ~ 1

Author(s):

H. Padalia ◽

P. P. Mondal

Keyword(s):

Time Series ◽

Spatial Clustering ◽

Spatial Scales ◽

Temporal Trends ◽

Fire Frequency ◽

Time Series Regression ◽

Slash And Burn ◽

Slash And Burn Agriculture ◽

Spatio Temporal ◽

In Fire

Increasing incidences of fire from land conversion and residue burning in tropics is the major concern in global warming. Spatial and temporal monitoring of trends of fire incidences is, therefore, significant in order to determine contribution of carbon emissions from slash and burn agriculture. In this study, we analyzed time-series Terra / Aqua MODIS satellite hotspot products from 2001 to 2013 to derive intra- and inter-annual trends in fire incidences in Nagaland state, located in the Indo-Burma biodiversity hotspot. Time-series regression was applied to MODIS fire products at variable spatial scales in GIS. Significance of change in fire frequency at each grid level was tested using t statistic. Spatial clustering of higher or lower fire incidences across study area was determined using Getis-OrdGi statistic. Maximum fire incidences were encountered in moist mixed deciduous forests (46%) followed by secondary moist bamboo brakes (30%). In most parts of the study area fire incidences peaked during March while in warmer parts (e.g. Mon district dominated by indigenous people) fire activity starts as early as during November and peaks in January. Regression trend analysis captured noticeable areas with statistically significant positive (e.g. Mokokchung, Wokha, Mon, Tuensang and Kiphire districts) and negative (e.g. Kohima and north-western part of Mokokchung district) inter-annual fire frequency trends based on area-based aggregation of fire occurrences at different grid sizes. Localization of spatial clusters of high fire incidences was observed in Mokokchung, Wokha, Mon,Tuensang and Kiphire districts.

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Climatic Factors Affecting The Population Dynamics Of Lentil Aphid In Inner Terai Region Of Nepal

SAARC Journal of Agriculture ◽

10.3329/sja.v17i2.45302 ◽

2020 ◽

Vol 17 (2) ◽

pp. 155-164

Author(s):

S Neupane ◽

S Subedi

Keyword(s):

Population Dynamics ◽

Relative Humidity ◽

Minimum Temperature ◽

Negative Impact ◽

Climatic Factors ◽

Block Design ◽

Winter Season ◽

Research Field ◽

Aphid Population ◽

Maximum Temperature

Population dynamics of lentil aphid Aphis craccivora (Hemiptera: Aphididae) was assessed in relation with climatic parameters at the research field of National Maize Research Program (NMRP), Rampur, Chitwan during winter season of two consecutive years 2016 to 2018. The experiment was organized in randomized complete block design consisting 20 lentil varieties with three replications. The crop was sown during last week of November in both the years. The daily meteorological parameters like maximum temperature (Tmax), minimum temperature (Tmin), relative humidity (RH) and rainfall (Rf) were recorded at the meteorological station located in NMRP, Rampur, Chitwan and then converted into weekly basis as the standard meteorological week (SMW) with correspondence to weekly population of aphid. The incidence of aphid was started from 2nd SMW of January (2 aphid/plant/10 cm apical twigs) during both experimentation years. Initially the population was low and gradually increased and reached to its peak (49 aphid/plant/10cm apical twigs) on 9th SMW i.e. first week of March with correspondence to weather parameters viz. maximum and minimum temperature (°C), relative humidity (%) and rainfall (mm) were 30.80, 15.34, 67.72 and 0, respectively over the years. The aphid population had significant positive correlation with Tmax (r= 0.94) while the Tmin showed highly significant correlation (r=0.99). The relative humidity (RH) had non significant negative correlation (r= -0.90) and rainfall (Rf) showed non significant negative impact (r= - 0.15) with aphid population. The regression model developed could explain 99% variation in aphid population in different cultivars of lentil. SAARC J. Agri., 17(2): 155-164 (2019)

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The 20-y spatio-temporal trends of remotely sensed soil moisture and vegetation and their response to climate change over the Third Pole

Journal of Hydrometeorology ◽

10.1175/jhm-d-21-0077.1 ◽

2021 ◽

Author(s):

Pengfei Shi ◽

Jiangyuan Zeng ◽

Kun-Shan Chen ◽

Hongliang Ma ◽

Haiyun Bi ◽

...

Keyword(s):

Soil Moisture ◽

Climatic Factors ◽

Temporal Trends ◽

Arid Zones ◽

The Tibetan Plateau ◽

Change Rate ◽

Vegetation Growth ◽

The Third ◽

Increasing Trend ◽

Spatio Temporal

AbstractThe Tibetan Plateau (TP), known as the “Third Pole”, is a climate-sensitive and ecology-fragile region. In this study, the spatio-temporal trends of soil moisture (SM) and vegetation were analyzed using satellite-based ESA CCI SM and MODIS LAI data respectively in the growing season during the last 20 years (2000-2019) over the TP covering diverse climate zones. The climatic drivers (precipitation and air temperature) of SM and LAI variations were fully investigated by using both ERA5 reanalysis and observation-based gridded data. The results reveal the TP is generally wetting and significantly greening in the last 20 years. The SM with significant increasing trend accounts for 21.80% (fraction of grid cells) of the TP, and is about twice of the SM with significant decreasing trend (10.19%), while more than half of the TP (58.21%) exhibits significant increasing trend of LAI. Though the responses of SM and LAI to climatic factors are spatially heterogeneous, precipitation is the dominant driver of SM variation with 48.36% (ERA5) and 32.51% (observation-based) precipitation data showing the strongest significant positive partial correlation with SM. Temperature rise largely explains the vegetation greening though precipitation also plays an important role in vegetation growth in arid and semi-arid zones. The combined trend of SM and LAI indicates the TP is mainly composed of wetting and greening areas, followed by drying and greening regions. The change rate of SM is negative at low altitudes and becomes positive as altitude increases, while the LAI value and its change rate decrease as altitude increases.

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Spatio-temporal variation of extreme indices derived from observed and reanalysis products for detection of climate change across India

10.5194/egusphere-egu2020-5837 ◽

2020 ◽

Author(s):

Sachidanand Kumar ◽

Kironmala Chanda ◽

Srinivas Pasupuleti

Keyword(s):

Climate Change ◽

Extreme Precipitation ◽

Daily Precipitation ◽

Temporal Trends ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Spatio Temporal ◽

Precipitation And Temperature

AbstractThis article reports the research findings in a recent study (Kumar et al., 2020) that utilizes eight indices of climate change recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) for analyzing spatio-temporal trends in extreme precipitation and temperature at the daily scale across India. Observed gridded precipitation (1971-2017) and temperature (1971-2013) datasets from India Meteorological Department (IMD) are used along with reanalysis products from Climate Prediction Centre (CPC). The trends are estimated using non-parametric Mann-Kendall (MK) test and regression analysis. The trends in &#8216;wet days&#8217; (daily precipitation greater than 95th percentile) and &#8216;dry days&#8217; (daily precipitation lower than 5th percentile) are examined considering the entire year (annual) as well as monsoon months only (seasonal). At the annual scale, about 13% of the grid locations indicated significant trend (either increasing or decreasing at 5% significance level) in the index R95p (rainfall contribution from extreme &#8216;wet days&#8217;) while 20% of the locations indicated significant trend in R5p (rainfall contribution from extreme &#8216;dry days&#8217;). For the seasonal analysis (June to September), the corresponding figures are nil and 21% respectively. The spatio-temporal trends in &#8216;warm days&#8217; (daily maximum temperature greater than 95th percentile), &#8216;warm nights&#8217; (daily minimum temperature greater than 95th percentile), &#8216;cold days&#8217; (daily maximum temperature lower than 5th percentile) and &#8216;cold nights&#8217; (daily minimum temperature lower than 5th percentile) are also investigated for the aforementioned period. The number of &#8216;warm days&#8217; per year increased significantly at 14% of the locations, while the number of &#8216;cold days&#8217;, &#8216;warm nights&#8217; and &#8216;cold nights&#8217; per year decreased significantly at several (42%, 34% and 39%) of the locations. The extreme temperature indices are also investigated for the future using CanESM2 projected data for RCP8.5 after suitable bias correction. Most of the locations (49% to 84%) indicate significant increasing (decreasing) trend in &#8216;warm days&#8217; (&#8216;cold days&#8217;) in the three epochs, 2006-2040, 2041-2070 and 2071-2100. Moreover, most locations (60% to 81%) show an increasing trend in &#8216;warm nights&#8217; and a decreasing trend in &#8216;cold nights&#8217; in all the epochs. A similar investigation for the historical and future periods using CPC data as the reference indicates that the trends, on comparison with IMD observations, seem to be in agreement for temperature extremes but spatially more extensive in case of CPC precipitation extremes.Keywords: extreme precipitation and temperature, climate change indices, spatio-temporal variation, IndiaReferences:Kumar S., Chanda, K., Srinivas P., (2020), Spatiotemporal analysis of extreme indices derived from daily precipitation and temperature for climate change detection over India, Theoretical and Applied Climatology, Springer, In press, DOI: 10.1007/s00704-020-03088-5.

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Basidiome production of ectomycorrhizal and saprophytic agaricoid fungi respond differently to forest management

Canadian Journal of Forest Research ◽

10.1139/cjfr-2018-0215 ◽

2020 ◽

Vol 50 (2) ◽

pp. 102-112

Author(s):

Gonzalo M. Romano ◽

Bernardo E. Lechner ◽

Alina G. Greslebin

Keyword(s):

Forest Management ◽

Relative Humidity ◽

Forest Structure ◽

Climatic Factors ◽

Tree Density ◽

Maximum Temperature ◽

Mean Annual Precipitation ◽

Site Conditions ◽

Nothofagus Pumilio ◽

Border Effects

Forest management generates border effects in mature dense forests. How agaricoid fungi species react to this disturbance depends on climatic and site conditions, as well as forest management system used and its intensity. We compared abundance and richness of ectomycorrhizal and saprophytic species in managed and unmanaged stands in Nothofagus pumilio (Poepp. & Endl.) Krasser forests of Patagonia, Argentina. We found that basidiome abundance and richness of ectomycorrhizal and saprophytic species were favoured by different forest structure and climatic factors. Ectomycorrhizal species basidiome production was significantly correlated to mean relative humidity of the 15 days prior to sampling and tree density (number of trees per hectare) existing prior to management activities. The latter implies that the tree density an ecosystem is capable of sustaining is crucial to the establishment of ectomycorrhizal species. Saprophytic species were favoured by the increased amount of woody material generated by logging together with maximum temperature in the 15 days prior to sampling and mean annual precipitation. Our results indicate that agaricoid fungi are not affected by low- to medium-intensity forest management, establishing the forestry level that fungal community can tolerate without loss of species in Patagonia.

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