scholarly journals Effects of climate variability and environmental factors on the spatiotemporal distribution of malaria incidence in the Amhara national regional state, Ethiopia

2021 ◽  
pp. 100475
Author(s):  
Teshager Zerihun Nigussie ◽  
Temesgen Zewotir ◽  
Essey Kebede Muluneh
Keyword(s):  
Environmental Factors ◽  
Climate Variability ◽  
Malaria Incidence ◽  
Spatiotemporal Distribution ◽  
Regional State

scholarly journals Associations between the spatiotemporal distribution of Kawasaki disease and environmental factors: evidence supporting a multifactorial etiologic model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tisiana Low ◽  
Brian W. McCrindle ◽  
Brigitte Mueller ◽  
Chun-Po S. Fan ◽  
Emily Somerset ◽  
...  
Keyword(s):  
Kawasaki Disease ◽  
Environmental Factors ◽  
Disease Model ◽  
Information Criterion ◽  
Developed Countries ◽  
Spatiotemporal Distribution ◽  
Atmospheric Concentration ◽  
Related Factors ◽  
Temporal Correlations ◽  
Intestinal Infections

AbstractThe etiology of Kawasaki Disease (KD), the most common cause of acquired heart disease in children in developed countries, remains elusive, but could be multifactorial in nature as suggested by the numerous environmental and infectious exposures that have previously been linked to its epidemiology. There is still a lack of a comprehensive model describing these complex associations. We present a Bayesian disease model that provides insight in the spatiotemporal distribution of KD in Canada from 2004 to 2017. The disease model including environmental factors had improved Watanabe-Akaike information criterion (WAIC) compared to the base model which included only spatiotemporal and demographic effects and had excellent performance in recapitulating the spatiotemporal distribution of KD in Canada (98% and 86% spatial and temporal correlations, respectively). The model suggests an association between the distribution of KD and population composition, weather-related factors, aeroallergen exposure, pollution, atmospheric concentration of spores and algae, and the incidence of healthcare encounters for bacterial pneumonia or viral intestinal infections. This model could be the basis of a hypothetical data-driven framework for the spatiotemporal distribution of KD. It also generates novel hypotheses about the etiology of KD, and provides a basis for the future development of a predictive and surveillance model.

scholarly journals Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model

2018 ◽  
Vol 10 (1) ◽  
pp. 88-100 ◽  
Author(s):  
Gbenga J. Abiodun ◽  
Peter J. Witbooi ◽  
Kazeem O. Okosun ◽  
Rajendra Maharaj
Keyword(s):  
Climate Variability ◽  
Malaria Transmission ◽  
Malaria Incidence ◽  
Principal Component ◽  
Wavelet Coherence ◽  
Human Malaria ◽  
Kwazulu Natal ◽  
The Impact ◽  
Wavelet Coherence Analysis ◽  
Malaria Model

Introduction: The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas. Methods: In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence. Results: Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.

scholarly journals Five-year Surveillance of Malaria in Hotspot and Ivermectin Mass-drug Administration Zone of Amhara Regional State, Ethiopia

2021 ◽  
Author(s):  
Chalachew Yenew ◽  
Sileshi Mulatu ◽  
Asaye Alamneh
Keyword(s):  
Data Analysis ◽  
Incidence Rate ◽  
Drug Administration ◽  
Mass Drug Administration ◽  
Malaria Incidence ◽  
Reduction Rate ◽  
Supportive Supervision ◽  
Standard Format ◽  
Regional State ◽  
Malaria Incidence Rate

Abstract Objectives: Evaluate the five-year surveillance of malaria in the hotspot and Ivermectin mass-drug administration Zone of Amhara Regional State, Ethiopia.Methods: - A descriptive prevalence study design was employed and incorporated 25 study health institutions into the survey using the purposive sampling technique. Data were obtained by the standard format of systematic evaluation of four surveillance units from January to August 2020 through observation, document review, and interviewing surveillance officers and focal persons using a semi-structured Survey and generated the statistical analysis, tabular, and graphical output using the open-source statistical program R. Results: - Average report fullness and aptness were 97.9% and 96% subsequently. The average annual malaria incidence rate declined in terms of place and time, from the year 2015 to 2019 with an average reduction rate of 5.5% and the average annual parasitic incidence rate was 52%. The study identifies high endemicity of malaria due to no program-specific supportive supervision of public health emergency management and no routine data analysis.Conclusions: This result revealed that the malaria incidence rate showed a remarkable decline. However, the annual parasitic incidence rate remains constant. The study also indicated that ivermectin did not affect malaria elimination. Hence, the districts and sub-city health offices should conduct regular surveillance data analysis, perform supportive supervision, avail budgets, and further laboratory investigations to investigate the effect of ivermectin on the parasites under laboratory conditions.

scholarly journals Effects of Socio-Environmental Factors on Malaria Infection in Pakistan: A Bayesian Spatial Analysis

2019 ◽  
Vol 16 (8) ◽  
pp. 1365 ◽  
Author(s):  
Muhammad Farooq Umer ◽  
Shumaila Zofeen ◽  
Abdul Majeed ◽  
Wenbiao Hu ◽  
Xin Qi ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Malaria Incidence ◽  
Meteorological Data ◽  
Random Effect ◽  
Control Program ◽  
Population Data ◽  
Mean Value ◽  
Malaria Control Program ◽  
Study Population ◽  
Bayesian Spatial Analysis

The role of socio-environmental factors in shaping malaria dynamics is complex and inconsistent. Effects of socio-environmental factors on malaria in Pakistan at district level were examined. Annual malaria cases data were obtained from Directorate of Malaria Control Program, Pakistan. Meteorological data were supplied by Pakistan Meteorological Department. A major limitation was the use of yearly, rather than monthly/weekly malaria data in this study. Population data, socio-economic data and education score data were downloaded from internet. Bayesian conditional autoregressive model was used to find the statistical association of socio-environmental factors with malaria in Pakistan. From 136/146 districts in Pakistan, >750,000 confirmed malaria cases were included, over a three years’ period (2013–2015). Socioeconomic status ((posterior mean value −3.965, (2.5% quintile, −6.297%), (97.5% quintile, −1.754%)) and human population density (−7.41 × 10−4, −0.001406%, −1.05 × 10−4 %) were inversely related, while minimum temperature (0.1398, 0.05275%, 0.2145%) was directly proportional to malaria in Pakistan during the study period. Spatial random effect maps presented that moderate relative risk (RR, 0.75 to 1.24) and high RR (1.25 to 1.99) clusters were scattered throughout the country, outnumbering the ones’ with low RR (0.23 to 0.74). Socio-environmental variables influence annual malaria incidence in Pakistan and needs further evaluation.

scholarly journals Climate Variability, Social and Environmental Factors, and Ross River Virus Transmission: Research Development and Future Research Needs

2008 ◽  
Vol 116 (12) ◽  
pp. 1591-1597 ◽  
Author(s):  
Shilu Tong ◽  
Pat Dale ◽  
Neville Nicholls ◽  
John S. Mackenzie ◽  
Rodney Wolff ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Climate Variability ◽  
Virus Transmission ◽  
Future Research ◽  
Ross River Virus ◽  
Research Needs ◽  
Research Development

scholarly journals Five Year Trend Analysis of Malaria Cases in Adama, Boset and Lume Districts of East Shawa, Oromia, Ethiopia

2021 ◽  
Author(s):  
Temesgen File Hulluka ◽  
Bayisa Chala Chala
Keyword(s):  
Malaria Transmission ◽  
Disease Burden ◽  
Malaria Incidence ◽  
Reduction Rate ◽  
Malaria Prevalence ◽  
Retrospective Data ◽  
Age Group ◽  
Malaria Epidemiology ◽  
Malaria Indicator Survey ◽  
Regional State

Abstract BackgroundMalaria is an infectious disease caused by Plasmodium parasites. Of the five human malaria parasites Plasmodium falciparum and Plasmodium vivax are the two co-endemic predominant and widely distributed species in Ethiopia greatly affecting public health and socio-economic development. Even though enormous effort have been made countrywide to reduce the disease burden little has been reported about trends of malaria transmission in the several localities of malarious areas like East Shawa Zone of Oromia Regional State, Ethiopia. Thus, the present study was aimed at assessing five- year (2016-2020) trends of malaria transmission at Adama, Boset and Lume districts of East Shawa Zone of Oromia Regional State, Ethiopia. MethodsRetrospective data were collected from the central surveillance of East Shawa Zone Health Office. The data collected was analyzed from September 2020 to December 2020 to examine trends of malaria epidemiology in three malarious districts in the Zone. The result shows, although a remarkable decrease in slide positivity rate (SPR) from (47.8 to 7.9%) and prevalence rate (6 to 1%) in the area, a recent slight increase of malaria SPR and prevalence was observed. Male individuals, particularly the productive section of the society (fifteen years and above age group) were more infected (60%), where falciparum, vivax and mixed malaria cases accounted for (53%), (41%), and (6%) respectively. Conclusion and Recommendations: Although reduction of malaria incidence was recorded in the study area, and higher malaria prevalence compared to the report of the national malaria indicator survey and inconsistency of the reduction rate noted in the study area demands due attention in the sector.

scholarly journals Earth observation in support of malaria control and epidemiology: MALAREO monitoring approaches

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonas Franke ◽  
Michael Gebreslasie ◽  
Ides Bauwens ◽  
Julie Deleu ◽  
Florian Siegert
Keyword(s):  
Environmental Factors ◽  
Vector Control ◽  
Malaria Control ◽  
Malaria Incidence ◽  
Modern Technology ◽  
Earth Observation ◽  
Malaria Vector Control ◽  
Support Vector ◽  
African Countries ◽  
Control Programmes

Malaria affects about half of the world’s population, with the vast majority of cases occuring in Africa. National malaria control programmes aim to reduce the burden of malaria and its negative, socioeconomic effects by using various control strategies (<em>e.g.</em> vector control, environmental management and case tracking). Vector control is the most effective transmission prevention strategy, while environmental factors are the key parameters affecting transmission. Geographic information systems (GIS), earth observation (EO) and spatial modelling are increasingly being recognised as valuable tools for effective management and malaria vector control. Issues previously inhibiting the use of EO in epidemiology and malaria control such as poor satellite sensor performance, high costs and long turnaround times, have since been resolved through modern technology. The core goal of this study was to develop and implement the capabilities of EO data for national malaria control programmes in South Africa, Swaziland and Mozambique. High- and very high resolution (HR and VHR) land cover and wetland maps were generated for the identification of potential vector habitats and human activities, as well as geoinformation on distance to wetlands for malaria risk modelling, population density maps, habitat foci maps and VHR household maps. These products were further used for modelling malaria incidence and the analysis of environmental factors that favour vector breeding. Geoproducts were also transferred to the staff of national malaria control programmes in seven African countries to demonstrate how EO data and GIS can support vector control strategy planning and monitoring. The transferred EO products support better epidemiological understanding of environmental factors related to malaria transmission, and allow for spatio-temporal targeting of malaria control interventions, thereby improving the cost-effectiveness of interventions.

Landsat-derived environmental factors to describe habitat preferences and spatiotemporal distribution of phytoplankton

2019 ◽  
Vol 408 ◽  
pp. 108759
Author(s):  
Miguel Ángel Matus-Hernández ◽  
Raúl Octavio Martínez-Rincón ◽  
Rosa Judith Aviña-Hernández ◽  
Norma Yolanda Hernández-Saavedra
Keyword(s):  
Environmental Factors ◽  
Habitat Preferences ◽  
Spatiotemporal Distribution
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