scholarly journals Lagged effects of rainfall on malaria: a case study of Meghalaya

2021 ◽  
Author(s):  
Holendro Singh Chungkham ◽  
Strong P Marbaniang ◽  
Hritiz Gogoi
Keyword(s):  
Malaria Transmission ◽  
Climatic Factors ◽  
Malaria Incidence ◽  
Climatic Conditions ◽  
Structural Time Series ◽  
Distributed Lag ◽  
Department Of Health ◽  
Non Linear ◽  
Malaria Death ◽  
Rainfall Level

Abstract Background: Meghalaya contributes about twenty per cent of India's total malaria death and is one of the high malaria endemic states in India, very susceptible to malaria transmission mainly due to favorable climatic conditions that mostly facilitate the transmission. In the relationship between malaria and meteorological factors, existing studies mainly focus on the interaction between different climatic factors, while interaction within one specific climatic predictor at different ag times has been largely neglected. This paper aims to explore the interaction of lagged rainfalls and their impact on malaria incidence. Methods: The district monthly malaria records from Jan 2005 to December 2017 was collected from the Department of Health Services (Malaria), Government of Meghalaya. The district monthly meteorological records from Jan 2005 to December 2017 was collected from the Directorate of Agriculture, Government of Meghalaya, in which average temperature (℃), humidity (%) and rainfall (mm) had been recorded. Monthly malaria cases and three climatic variables of 4 districts in Meghalaya from 2015 to 2017 were analysed with the varying coefficient-distributed lag non-linear model. The missing climatic values were imputed using Kalman Smoothing on structural time series using the package imputeTS in R. Results: During the period 2005-2017, a total of 309133 malaria cases were reported in all the districts under study. The monthly average rainfall ranges from a minimum of 181.79 mm in South Garo to a maximum of 367.87 in Jaintia. Also, South Garo and East Khasi are the hottest and the coolest place understudy with 26.96 and 16.86 degrees Celsius respectively. Rainfall levels in the first-month lag affect the non-linear patterns between the incidence of malaria and rainfall at each lag time. The low rainfall level at the first-month lag may promote malaria incidence as rainfall increases. However, for the high rainfall level at the first-month lag, malaria incidence decreases as rainfall increases. Conclusion: The interaction effect between lagged rainfalls on malaria incidence was observed in this study, and highlights its importance for future studies to better understand and predict malaria transmission.

Assessment of malaria incidence using the Richards model in Arunachal Pradesh, India

2014 ◽  
Vol 142 (10) ◽  
pp. 2227-2236 ◽  
Author(s):  
M. SRINIVASA RAO ◽  
U. SURYANARYANA MURTY ◽  
K. MADHUSUDHAN RAO ◽  
N. KARTIK ◽  
G. PREEYANTEE ◽  
...  
Keyword(s):  
Malaria Transmission ◽  
Climatic Factors ◽  
Malaria Incidence ◽  
Climatic Conditions ◽  
Transmission Dynamics ◽  
High Morbidity ◽  
Suitable Model ◽  
Arunachal Pradesh ◽  
Wet Season ◽  
Richards Model

SUMMARYMonitoring of malaria intensity in terrain regions of Arunachal Pradesh, India is very difficult as the dynamics of mosquito populations varies to a large extent due to altitude and frequent changes in climatic conditions. There is a scarcity of information on the influence of climatic factors on malaria morbidity in Arunachal Pradesh. Hence, a pilot study was conducted from 2006 to 2010 to understand malaria transmission dynamics, seasonal distribution and disease morbidity. Plasmodium vivax and P. falciparum are the two major parasites for malaria transmission in Arunachal Pradesh. Out of 142 558 malaria cases analysed from 2006 to 2010, P. vivax infection contributed 72·1% followed by P. falciparum (27·9%). However, the overall morbidity of malaria declined from 37/1000 in 2006 to 18/1000 population in 2010. From this study it was observed that the temporal distribution of malaria cases varied between districts and high morbidity rates were reported mostly during the wet season. To understand malaria transmission dynamics in the study area, the Richards model was used to predict malaria cases. The output of the results from this model predicted a higher number of malaria cases (K) during 2006 and a gradual decline in subsequent years. Similarly, the growth rate r, and exponential deviation α, were almost identical for all the years, which shows that the Richards model is the most suitable model for the prediction of malaria cases.

scholarly journals Associations between environmental covariates and temporal changes in malaria incidence in high transmission settings of Uganda: a distributed lag nonlinear analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jaffer Okiring ◽  
Isobel Routledge ◽  
Adrienne Epstein ◽  
Jane F. Namuganga ◽  
Emmanuel V. Kamya ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Malaria Transmission ◽  
Malaria Incidence ◽  
Critical Role ◽  
Environmental Data ◽  
Environmental Covariates ◽  
High Transmission ◽  
Monthly Temperature ◽  
Distributed Lag ◽  
Catchment Areas

Abstract Background Environmental factors such as temperature, rainfall, and vegetation cover play a critical role in malaria transmission. However, quantifying the relationships between environmental factors and measures of disease burden relevant for public health can be complex as effects are often non-linear and subject to temporal lags between when changes in environmental factors lead to changes in malaria incidence. The study investigated the effect of environmental covariates on malaria incidence in high transmission settings of Uganda. Methods This study leveraged data from seven malaria reference centres (MRCs) located in high transmission settings of Uganda over a 24-month period. Estimates of monthly malaria incidence (MI) were derived from MRCs’ catchment areas. Environmental data including monthly temperature, rainfall, and normalized difference vegetation index (NDVI) were obtained from remote sensing sources. A distributed lag nonlinear model was used to investigate the effect of environmental covariates on malaria incidence. Results Overall, the median (range) monthly temperature was 30 °C (26–47), rainfall 133.0 mm (3.0–247), NDVI 0.66 (0.24–0.80) and MI was 790 per 1000 person-years (73–3973). Temperature of 35 °C was significantly associated with malaria incidence compared to the median observed temperature (30 °C) at month lag 2 (IRR: 2.00, 95% CI: 1.42–2.83) and the increased cumulative IRR of malaria at month lags 1–4, with the highest cumulative IRR of 8.16 (95% CI: 3.41–20.26) at lag-month 4. Rainfall of 200 mm significantly increased IRR of malaria compared to the median observed rainfall (133 mm) at lag-month 0 (IRR: 1.24, 95% CI: 1.01–1.52) and the increased cumulative IRR of malaria at month lags 1–4, with the highest cumulative IRR of 1.99(95% CI: 1.22–2.27) at lag-month 4. Average NVDI of 0.72 significantly increased the cumulative IRR of malaria compared to the median observed NDVI (0.66) at month lags 2–4, with the highest cumulative IRR of 1.57(95% CI: 1.09–2.25) at lag-month 4. Conclusions In high-malaria transmission settings, high values of environmental covariates were associated with increased cumulative IRR of malaria, with IRR peaks at variable lag times. The complex associations identified are valuable for designing strategies for early warning, prevention, and control of seasonal malaria surges and epidemics.

scholarly journals Associations between environmental covariates and malaria incidence in high transmission settings of Uganda: A distributed non-linear lagged ecological analysis

2021 ◽  
Author(s):  
Jaffer Okiring ◽  
Isobel Routledge ◽  
Adrienne Esptein ◽  
Jane F. Namuganga ◽  
Emmanuel V. Kamya ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Malaria Transmission ◽  
Malaria Incidence ◽  
Environmental Data ◽  
Environmental Covariates ◽  
High Transmission ◽  
Monthly Temperature ◽  
Rate Of Increase ◽  
Catchment Areas ◽  
Non Linear

Abstract Background Environmental factors such as temperature, rainfall, and vegetation cover play a critical role in malaria transmission. However, quantifying the relationships between environmental factors and measures of disease burden relevant for public health can be complex as effects are often non-linear and subject to temporal lags between when changes in environmental factors lead to changes in the incidence of symptomatic malaria. The study aim was to investigate the associations between environmental covariates and malaria incidence in high transmission settings of Uganda.Methods This study leveraged data from seven malaria reference centres (MRCs) located in high transmission settings of Uganda over a 24-month period (January 2019 - December 2020). Estimates of monthly malaria incidence (MI) were derived from MRCs’ catchment areas. Environmental data including monthy average measures of temperature, rainfall, and normalized difference vegetation index (NDVI) were obtained from remote sensing sources. A distributed non-linear lagged model was used to investigate the quantitative relationship between environmental covariates and malaria incidence. Results Overall, the median (range) monthly temperature was 30oC (26-47), rainfall 133.0 mm (3.0-247), NDVI 0.66 (0.24-0.80) and MI was 790 per 1000 person-years (73-3973). A non-linear relationship between environmental covariates and malaria incidence was observed. An average monthly temperature of 35oC was associated with significant increases in malaria incidence compared to the median observed temperature (30oC) at month lag 2 (IRR: 2.00, 95% CI: 1.42-2.83) and the cumulative increases in MI significantly at month lags 1-4, with the highest cumulative IRR of 8.16 (95% CI: 3.41-20.26) at lag month 4. An average monthly rainfall of 200mm was associated with significant increases in malaria incidence compared to the median observed rainfall (133mm) at lag month 0 (IRR: 1.24, 95% CI: 1.01-1.52) and the cumulative IRR increases of malaria at month lags 1-4, with the highest cumulative IRR of 1.99(95% CI: 1.22-2.27) at lag month 4. An average NVDI of 0.72 was associated with significant cumulative increases in IRR of malaria as compared to the median observed NDVI (0.66) at month lag 2-4, with the highest cumulative IRR of 1.57(95% CI: 1.09-2.25) at lag month 4. The rate of increase in cumulative IRR of malaria was highest within lag months 1-2 as compared to lag months 3-4 for all the environmental covariates.Conclusions In high-malaria transmission settings, high values of environmental covariates were associated with cumulative increases in the incidence of malaria, with peak associations occurring after variable lag times. The complex associations identified are valuable for designing strategies for early warning, prevention, and control of seasonal malaria surges and epidemics.

scholarly journals Radial Growth Response of European Larch Provenances to Interannual Climate Variation in Poland

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 334
Author(s):  
Norbert Szymański ◽  
Sławomir Wilczyński
Keyword(s):  
Radial Growth ◽  
Climatic Factors ◽  
Principal Component ◽  
Climatic Conditions ◽  
Growth Responses ◽  
European Larch ◽  
Temperature And Precipitation ◽  
Provenance Trials ◽  
High Precipitation ◽  
Climatic Elements

The present study identified the similarities and differences in the radial growth responses of 20 provenances of 51-year-old European larch (Larix decidua Mill.) trees from Poland to the climatic conditions at three provenance trials situated in the Polish lowlands (Siemianice), uplands (Bliżyn) and mountains (Krynica). A chronology of radial growth indices was developed for each of 60 European larch populations, which highlighted the interannual variations in the climate-mediated radial growth of their trees. With the aid of principal component, correlation and multiple regression analysis, supra-regional climatic elements were identified to which all the larch provenances reacted similarly at all three provenance trials. They increased the radial growth in years with a short, warm and precipitation-rich winter; a cool and humid summer and when high precipitation in late autumn of the previous year was noted. Moreover, other climatic elements were identified to which two groups of the larch provenances reacted differently at each provenance trial. In the lowland climate, the provenances reacted differently to temperature in November to December of the previous year and July and to precipitation in September. In the upland climate, the provenances differed in growth sensitivity to precipitation in October of the previous year and June–September. In the mountain climate, the provenances responded differently to temperature and precipitation in September of the previous year and to precipitation in February, June and September of the year of tree ring formation. The results imply that both climatic factors and origin (genotype), i.e., the genetic factor, mediate the climate–growth relationships of larch provenances.

Impact of climatic conditions on the parameters of failure flow of military vehicles

2021 ◽  
pp. 095440702110202
Author(s):  
Nikolaj Dobrzinskij ◽  
Algimantas Fedaravicius ◽  
Kestutis Pilkauskas ◽  
Egidijus Slizys
Keyword(s):  
Climatic Factors ◽  
Armed Forces ◽  
Climatic Conditions ◽  
Operating Conditions ◽  
Technical Equipment ◽  
Factors Affecting ◽  
Military Vehicles ◽  
Equipment Reliability ◽  
Number Of Factors ◽  
The Impact

Relevance of the article is based on participation of armed forces in various operations and exercises, where reliability of machinery is one of the most important factors. Transportation of soldiers as well as completion of variety of tasks is ensured by properly functioning technical equipment. Reliability of military vehicles – armoured SISU E13TP Finnish built and HMMWV M1025 USA built were selected as the object of the article. Impact of climatic conditions on reliability of the vehicles exploited in southwestern part of the Atlantic continental forest area is researched by a case study of the vehicles exploitation under conditions of the climate of Lithuania. Reliability of military vehicles depends on a number of factors such as properties of the vehicles and external conditions of their operation. Their systems and mechanisms are influenced by a number of factors that cause different failures. Climatic conditions represent one of the factors of operating load which is directly dependent on the climate zone. Therefore, assessment of the reliability is started with the analysis of climatic factors affecting operating conditions of the vehicles. Relationship between the impact of climatic factors and failure flow of the vehicles is presented and discussed.

scholarly journals Improved Rice Technology Adoption: The Role of Spatially-Dependent Risk Preference

Agriculture ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 691
Author(s):  
Omotuyole Isiaka Ambali ◽  
Francisco Jose Areal ◽  
Nikolaos Georgantzis
Keyword(s):  
Field Experiments ◽  
Climatic Factors ◽  
Risk Preferences ◽  
Risk Preference ◽  
Probit Model ◽  
Climatic Conditions ◽  
High Yield ◽  
Risk Attitudes ◽  
Policy Action ◽  
Rice Varieties

This study analyses farmers’ adoption of improved rice technology, taking into account farmers’ risk preferences; the unobserved spatial heterogeneity associated with farmers’ risk preferences; farmers’ household and farm characteristics; farm locations, farmers’ access to information, and their perceptions on the rice improved varieties (i.e., high yield varieties, HYV). The study used data obtained from field experiments and a survey conducted in 2016 in Nigeria. An instrumental-variable probit model was estimated to account for potential endogenous farmers’ risk preference in the adoption decision model. Results show that risk averse (risk avoidant) farmers are less likely to adopt HYV, with the spatial lags of farmers’ risk attitudes found to be a good instrument for spatially unobserved variables (e.g., environmental and climatic factors). We conclude that studies supporting policy action aiming at the diffusion of improved rice varieties need to collect information, if possible, on farmers’ risk attitudes, local environmental and climatic conditions (e.g., climatic, topographic, soil quality, pest incidence) in order to ease the design and evaluation of policy actions on the adoption of improved agricultural technology.

Spatiotemporal distributed lag modelling of multiple Plasmodium species in a malaria elimination setting

2021 ◽  
Vol 30 (1) ◽  
pp. 22-34
Author(s):  
Chawarat Rotejanaprasert ◽  
Duncan Lee ◽  
Nattwut Ekapirat ◽  
Prayuth Sudathip ◽  
Richard J Maude
Keyword(s):  
Data Streams ◽  
Malaria Elimination ◽  
Parasite Species ◽  
Climatic Factors ◽  
Plasmodium Species ◽  
Clinical Malaria ◽  
Spatiotemporal Patterns ◽  
Distributed Lag ◽  
Multiple Data

In much of the Greater Mekong Sub-region, malaria is now confined to patches and small foci of transmission. Malaria transmission is seasonal with the spatiotemporal patterns being associated with variation in environmental and climatic factors. However, the possible effect at different lag periods between meteorological variables and clinical malaria has not been well studied in the region. Thus, in this study we developed distributed lagged modelling accounting for spatiotemporal excessive zero cases in a malaria elimination setting. A multivariate framework was also extended to incorporate multiple data streams and investigate the spatiotemporal patterns from multiple parasite species via their lagged association with climatic variables. A simulation study was conducted to examine robustness of the methodology and a case study is provided of weekly data of clinical malaria cases at sub-district level in Thailand.

Influence of Natural and Climatic Factors on Water Horizons Protection Degree in Site Evaluation for Radioactive Waste Disposal

2021 ◽  
Vol 24 (3) ◽  
pp. 301-310
Author(s):  
N. V. Harbachova ◽  
N. D. Kuzmina ◽  
N. V. Kulich ◽  
S. N. Yatsko ◽  
J. A. Korchova
Keyword(s):  
Radioactive Waste ◽  
Climatic Factors ◽  
Probabilistic Approach ◽  
Groundwater Vulnerability ◽  
Climatic Conditions ◽  
Radioactive Waste Disposal ◽  
Climatic Impact ◽  
Influence Zone ◽  
Site Evaluation ◽  
Numerical And Analytical Methods

In this paper, natural (geological and hydrological) and climatic impact conditions on the influence zone for two different sites of radioactive waste disposals have been studied. Probabilistic approach to assessment of the groundwater vulnerability from radionuclide contamination during disposal of radioactive waste is developed. As to climatic conditions, an effective numerical and analytical methods for annual precipitation rates assessment of rare recurrence have been proposed which allow to take into account uncertainties of rare events as well.

ASSESSMENT OF THE INFLUENCE OF THE MAIN CLIMATIC FACTORS ON THE YIELD OF WINTER CEREAL CROPS ON THE TERRITORY OF BELARUS FOR FORECASTING PURPOSES

2021 ◽  
pp. 41-48
Author(s):  
Halina A. Kamyshenka
Keyword(s):  
Computational Models ◽  
Climatic Factors ◽  
Climatic Conditions ◽  
Yield Variability ◽  
Cereal Crops ◽  
Winter Rye ◽  
Statistical Assessment ◽  
Winter Cereal ◽  
Temperature And Precipitation

The results of a statistical assessment of the influence of changing weather and climatic conditions of the territory of Belarus on the productivity of the main winter cereal crops are presented in order to build computational models of productivity. The calculations were made with respect to the climatic component as a predictor, taking into account the deviations of air temperature and precipitation from the long-term climatic norm of months that have the most significant effect on the yield of the studied crops. For winter rye and wheat, adequate models of yield variability have been built. The research results are relevant for solving forecasting problems.

scholarly journals Effect of Climatic Factors on Stem Biomass and Carbon Stock of Larix gmelinii and Betula platyphylla in Daxing’anling Mountain of Inner Mongolia, China

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Dilawar Khan ◽  
Muhammad Atif Muneer ◽  
Zaib-Un- Nisa ◽  
Sher Shah ◽  
Muhammad Amir ◽  
...  
Keyword(s):  
Inner Mongolia ◽  
Negative Impact ◽  
Climatic Factors ◽  
High Temperature Stress ◽  
Climatic Conditions ◽  
Larix Gmelinii ◽  
Maximum Temperature ◽  
Betula Platyphylla ◽  
Stem Biomass ◽  
Annual Minimum Temperature

Climate change has become a global concern for scientists as it is affecting almost every ecosystem. Larix gmelinii and Betula platyphylla are native and dominant forest species in the Daxing’anling Mountains of Inner Mongolia, playing a major role in carbon sequestration of this region. This study was carried out to assess the effect of climate variables including precipitation and temperature on the biomass of Larix gmelinii and Betula platyphylla forests. For this purpose, we used the climate-sensitive stem biomass allometric model for both species separately to find out accurate stem biomass along with climatic factors from 1950 to 2016. A total of 66 random plots were taken to attain the data from this study area. Larix gmelinii and Betula platyphylla stem biomass have a strong correlation with annual precipitation (R2 = 0.86, R2 = 0.71, R2 = 0.79, and R2 = 0.59) and maximum temperature (R2 = 0.76, R2 = 0.64, R2 = 0.67, and R2 = 0.52). However, annual minimum temperature (R2 = 0.58, R2 = 0.43, R2 = 0.55, and R2 = 0.46) and annual mean temperature (R2 = 0.40, R2 = 0.22, R2 = 0.36, and R2 = 0.19) have a relatively negative impact on tree biomass. Therefore, we suggest that both species have a very strong adaptive nature with climatic variation and hence can survive under drought and high-temperature stress climatic conditions.

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