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Image signal-to-noise ratio and noise variance estimation using autoregressive model

Kamel NS, Sim KS

Scanning, 2004 12 23;26(6):277-81.
PMID: 15612204

During the last three decades, several techniques have been proposed for signal-to-noise ratio (SNR) and noise variance estimation in images, with different degrees of success. Recently, a novel technique based on the statistical autoregressive model (AR) was developed and proposed as a solution to SNR estimation in scanning electron microscope (SEM) image. In this paper, the efficiency of the developed technique with different imaging systems is proven and presented as an optimum solution to image noise variance and SNR estimation problems. Simulation results are carried out with images like Lena, remote sensing, and SEM. The two image parameters, SNR and noise variance, are estimated using different techniques and are compared with the AR-based estimator.

Matched MeSH terms: Models, Statistical
Fulltext Removal of shells in palm kernel cake via static cling and electrostatic separation

Norhani Abdullah, Muhamad Akhmal Hakim Roslan, Shuhaimi Mustafa

Journal of Biochemistry, Microbiology and Biotechnology, 2015;3(1):1-6.
MyJurnal

Palm kernel cake (PKC), a by-product of the palm oil industry is limited in its use as a feed ingredient for poultry due to its high fibre and lignin content. The presence of these antinutritive components is the result of shells contaminating the by-product. The nutritive value of PKC has to be improved in order to increase its inclusion rate in poultry diet. In this study, PKC was subjected to a separation method using static cling and electrostatic separation to removethe shells present in PKC. Response surface methodology based on Box-Behnken design was used to optimize the separation method with moisture content (8 to 18%), particle size distribution (0.5 to 2.5 mm) and feed rate (20 to 200 g/min) as the independent variables evaluated. According to the regression coefficients and significance of the quadratic polynomial model, the optimum separation parameters were as follows: 13% PKC moisture content;

Matched MeSH terms: Models, Statistical
Fulltext Dimensional model for estimating factors influencing childhood obesity: path analysis based modeling

Kheirollahpour M, Shohaimi S

ScientificWorldJournal, 2014;2014:512148.
PMID: 25097878 DOI: 10.1155/2014/512148

The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI) of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA) was applied to reveal the hidden (secondary) effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model.

Matched MeSH terms: Models, Statistical*
Fulltext Network analysis of the depressive symptom profiles in Asian patients with depressive disorders: Findings from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP-AD)

Park SC, Jang EY, Xiang YT, Kanba S, Kato TA, Chong MY, et al.

Psychiatry Clin Neurosci, 2020 Jun;74(6):344-353.
PMID: 32048773 DOI: 10.1111/pcn.12989

AIM: We aimed to estimate the network structures of depressive symptoms using network analysis and evaluated the geographic regional differences in theses network structures among Asian patients with depressive disorders.
METHODS: Using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP-AD), the network of the ICD-10 diagnostic criteria for depressive episode was estimated from 1174 Asian patients with depressive disorders. The node strength centrality of all ICD-10 diagnostic criteria for a depressive episode was estimated using a community-detection algorithm. In addition, networks of depressive symptoms were estimated separately among East Asian patients and South or Southeast Asian patients. Moreover, networks were estimated separately among Asian patients from high-income countries and those from middle-income countries.
RESULTS: Persistent sadness, fatigue, and loss of interest were the most centrally situated within the network of depressive symptoms in Asian patients with depressive disorders overall. A community-detection algorithm estimated that when excluding psychomotor disturbance as an outlier, the other nine symptoms formed the largest clinically meaningful cluster. Geographic and economic variations in networks of depressive symptoms were evaluated.
CONCLUSION: Our findings demonstrated that the typical symptoms of the ICD-10 diagnostic criteria for depressive episode are the most centrally situated within the network of depressive symptoms. Furthermore, our findings suggested that cultural influences related to geographic and economic distributions of participants could influence the estimated depressive symptom network in Asian patients with depressive disorders.

Matched MeSH terms: Models, Statistical*
Influence of initial dissolved oxygen concentration on Fenton's reagent degradation

Aris A, Sharratt PN

Environ Technol, 2006 Oct;27(10):1153-61.
PMID: 17144264

The effect of initial dissolved oxygen concentration (IDOC) on Fenton's reagent degradation of a dyestuff, Reactive Black 5 was explored in this study. The study was designed, conducted and analysed based on Central Composite Rotatable Design using a 3-1 lab-scale reactor. The participation of O2 in the process was experimentally observed and appears to be affected by the dosage of the reagents used in the study. The IDOC was found to have a significant influence on the process. Reducing the IDOC from 7.5 mg l(-1) to 2.5 mg l(-1) increased the removal of TOC by an average of about 10%. Reduction of IDOC from 10 mg l(-1) to 0 mg l(-1) enhanced the TOC removal by about 30%. The negative influence of IDOC is likely to be caused by the competition between the O2 and the reagents for the organoradicals. A model describing the relationship between initial TOC removal, reagent dosage and IDOC has also been developed.

Matched MeSH terms: Models, Statistical
Determination of biochemical oxygen demand and dissolved oxygen for semi-arid river environment: application of soft computing models

Tao H, Bobaker AM, Ramal MM, Yaseen ZM, Hossain MS, Shahid S

Environ Sci Pollut Res Int, 2019 Jan;26(1):923-937.
PMID: 30421367 DOI: 10.1007/s11356-018-3663-x

Surface and ground water resources are highly sensitive aquatic systems to contaminants due to their accessibility to multiple-point and non-point sources of pollutions. Determination of water quality variables using mathematical models instead of laboratory experiments can have venerable significance in term of the environmental prospective. In this research, application of a new developed hybrid response surface method (HRSM) which is a modified model of the existing response surface model (RSM) is proposed for the first time to predict biochemical oxygen demand (BOD) and dissolved oxygen (DO) in Euphrates River, Iraq. The model was constructed using various physical and chemical variables including water temperature (T), turbidity, power of hydrogen (pH), electrical conductivity (EC), alkalinity, calcium (Ca), chemical oxygen demand (COD), sulfate (SO4), total dissolved solids (TDS), and total suspended solids (TSS) as input attributes. The monthly water quality sampling data for the period 2004-2013 was considered for structuring the input-output pattern required for the development of the models. An advance analysis was conducted to comprehend the correlation between the predictors and predictand. The prediction performances of HRSM were compared with that of support vector regression (SVR) model which is one of the most predominate applied machine learning approaches of the state-of-the-art for water quality prediction. The results indicated a very optimistic modeling accuracy of the proposed HRSM model to predict BOD and DO. Furthermore, the results showed a robust alternative mathematical model for determining water quality particularly in a data scarce region like Iraq.

Matched MeSH terms: Models, Statistical*
Wavelet neural networks applied to pulping of oil palm fronds

Zainuddin Z, Wan Daud WR, Pauline O, Shafie A

Bioresour Technol, 2011 Dec;102(23):10978-86.
PMID: 21996481 DOI: 10.1016/j.biortech.2011.09.080

In the organosolv pulping of the oil palm fronds, the influence of the operational variables of the pulping reactor (viz. cooking temperature and time, ethanol and NaOH concentration) on the properties of the resulting pulp (yield and kappa number) and paper sheets (tensile index and tear index) was investigated using a wavelet neural network model. The experimental results with error less than 0.0965 (in terms of MSE) were produced, and were then compared with those obtained from the response surface methodology. Performance assessment indicated that the neural network model possessed superior predictive ability than the polynomial model, since a very close agreement between the experimental and the predicted values was obtained.

Matched MeSH terms: Models, Statistical
Identifying gait asymmetry using gyroscopes--a cross-correlation and Normalized Symmetry Index approach

Gouwanda D, Senanayake SM

J Biomech, 2011 Mar 15;44(5):972-8.
PMID: 21306714 DOI: 10.1016/j.jbiomech.2010.12.013

Injury to a lower limb may disrupt natural walking and cause asymmetrical gait, therefore assessing the gait asymmetry has become one of the important procedures in gait analysis. This paper proposes the use of wireless gyroscopes as a new instrument to determine gait asymmetry. It also introduces two novel approaches: normalized cross-correlations (Cc(norm)) and Normalized Symmetry Index (SI(norm)). Cc(norm) evaluates the waveform patterns generated by the lower limb in each gait cycle. SI(norm) provides indications on the timing and magnitude of the bilateral differences between the limbs while addressing the drawbacks of the conventional methods. One-way ANOVA test reveals that Cc(norm) can be considered as single value indicator that determines the gait asymmetry (p<0.01). The experiment results showed that SI(norm) in asymmetrical gait were different from normal gait. SI(norm) in asymmetrical gait were found to be approximately 20% greater than SI(norm) in normal gait during pre-swing and initial swing.

Matched MeSH terms: Models, Statistical
The development of a tool to predict temperature-exposure of incinerated teeth using colourimetric and hydroxyapatite crystal size data

Rahmat RA, Humphries MA, Austin JJ, Linacre AMT, Self P

Int J Legal Med, 2021 Sep;135(5):2045-2053.
PMID: 33655354 DOI: 10.1007/s00414-021-02538-7

This study presents a novel tool to predict temperature-exposure of incinerated pig teeth as a proxy for understanding impacts of fire on human teeth. Previous studies on the estimation of temperature-exposure of skeletal elements have been limited to that of heat-exposed bone. This predictive tool was developed using a multinomial regression model of colourimetric and hydroxyapatite crystal size variables using data obtained from unheated pig teeth and teeth incinerated at 300 °C, 600 °C, 800 °C and 1000 °C. An additional variable based on the observed appearance of the tooth was included in the tool. This enables the tooth to be classified as definitely burnt (600 °C-1000 °C) or uncertain (27 °C/300 °C). As a result, the model predicting the temperature-exposure of the incinerated teeth had an accuracy of 95%. This tool is a holistic, robust and reliable approach to estimate temperature of heat-exposed pig teeth, with high accuracy, and may act as a valuable proxy to estimate heat exposure for human teeth in forensic casework.

Matched MeSH terms: Models, Statistical
Parceling Cannot Reduce Factor Indeterminacy in Factor Analysis: A Research Note

Rigdon EE, Becker JM, Sarstedt M

Psychometrika, 2019 09;84(3):772-780.
PMID: 31292860 DOI: 10.1007/s11336-019-09677-2

Parceling-using composites of observed variables as indicators for a common factor-strengthens loadings, but reduces the number of indicators. Factor indeterminacy is reduced when there are many observed variables per factor, and when loadings and factor correlations are strong. It is proven that parceling cannot reduce factor indeterminacy. In special cases where the ratio of loading to residual variance is the same for all items included in each parcel, factor indeterminacy is unaffected by parceling. Otherwise, parceling worsens factor indeterminacy. While factor indeterminacy does not affect the parameter estimates, standard errors, or fit indices associated with a factor model, it does create uncertainty, which endangers valid inference.

Matched MeSH terms: Models, Statistical
Forecasting asthma-related hospital admissions in London using negative binomial models

Soyiri IN, Reidpath DD, Sarran C

Chron Respir Dis, 2013 May;10(2):85-94.
PMID: 23620439 DOI: 10.1177/1479972313482847

Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.

Matched MeSH terms: Models, Statistical
Application of Box-Behnken design for ultrasound-assisted extraction and recycling preparative HPLC for isolation of anthraquinones from Cassia singueana

Jibril S, Basar N, Sirat HM, Wahab RA, Mahat NA, Nahar L, et al.

Phytochem Anal, 2019 Jan;30(1):101-109.
PMID: 30288828 DOI: 10.1002/pca.2795

INTRODUCTION: Cassia singueana Del. (Fabaceae) is a rare medicinal plant used in the traditional medicine preparations to treat various ailments. The root of C. singueana is a rich source of anthraquinones that possess anticancer, antibacterial and antifungal properties.
OBJECTIVE: The objective of this study was to develop an ultrasound-assisted extraction (UAE) method for achieving a high extraction yield of anthraquinones using the response surface methodology (RSM), Box-Behnken design (BBD), and a recycling preparative high-performance liquid chromatography (HPLC) protocol for isolation of anthraquinones from C. singueana.
METHODOLOGY: Optimisation of UAE was performed using the Box-Behnken experimental design. Recycling preparative HPLC was employed to isolate anthraquinones from the root extract of C. singueana.
RESULTS: The BBD was well-described by a quadratic polynomial model (R2 = 0.9751). The predicted optimal UAE conditions for a high extraction yield were obtained at: extraction time 25.00 min, temperature 50°C and solvent-sample ratio of 10 mL/g. Under the predicted conditions, the experimental value (1.65 ± 0.07%) closely agreed to the predicted yield (1.64%). The obtained crude extract of C. singueana root was subsequently purified to afford eight anthraquinones.
CONCLUSION: The extraction protocol described here is suitable for large-scale extraction of anthraquinones from plant extracts.

Matched MeSH terms: Models, Statistical
Fulltext Hybrid support vector regression and autoregressive integrated moving average models improved by particle swarm optimization for property crime rates forecasting with economic indicators

Alwee R, Shamsuddin SM, Sallehuddin R

ScientificWorldJournal, 2013;2013:951475.
PMID: 23766729 DOI: 10.1155/2013/951475

Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.

Matched MeSH terms: Models, Statistical*
Improved cellulase production by Botryosphaeria rhodina from OPEFB at low level moisture condition through statistical optimization

Bahrin EK, Ibrahim MF, Abd Razak MN, Abd-Aziz S, Shah UK, Alitheen N, et al.

Prep Biochem Biotechnol, 2012;42(2):155-70.
PMID: 22394064 DOI: 10.1080/10826068.2011.585413

The response surface method was applied in this study to improve cellulase production from oil palm empty fruit bunch (OPEFB) by Botryosphaeria rhodina. An experimental design based on a two-level factorial was employed to screen the significant environmental factors for cellulase production. The locally isolated fungus Botryosphaeria rhodina was cultivated on OPEFB under solid-state fermentation (SSF). From the analysis of variance (ANOVA), the initial moisture content, amount of substrate, and initial pH of nutrient supplied in the SSF system significantly influenced cellulase production. Then the optimization of the variables was done using the response surface method according to central composite design (CCD). Botryosphaeria rhodina exhibited its best performance with a high predicted value of FPase enzyme production (17.95 U/g) when the initial moisture content was at 24.32%, initial pH of nutrient was 5.96, and 3.98 g of substrate was present. The statistical optimization from actual experiment resulted in a significant increment of FPase production from 3.26 to 17.91 U/g (5.49-fold). High cellulase production at low moisture content is a very rare condition for fungi cultured in solid-state fermentation.

Matched MeSH terms: Models, Statistical
The effects of drainage basin geomorphometry on minimum low flow discharge: the study of small watershed in Kelang River Valley in Peninsular Malaysia

Yunus AJ, Nakagoshi N, Salleh KO

J Environ Sci (China), 2003 Mar;15(2):249-62.
PMID: 12765268

This study investigate the relationships between geomorphometric properties and the minimum low flow discharge of undisturbed drainage basins in the Taman Bukit Cahaya Seri Alam Forest Reserve, Peninsular Malaysia. The drainage basins selected were third-order basins so as to facilitate a common base for sampling and performing an unbiased statistical analyses. Three levels of relationships were observed in the study. Significant relationships existed between the geomorphometric properties as shown by the correlation network analysis; secondly, individual geomorphometric properties were observed to influence minimum flow discharge; and finally, the multiple regression model set up showed that minimum flow discharge (Q min) was dependent of basin area (AU), stream length (LS), maximum relief (Hmax), average relief (HAV) and stream frequency (SF). These findings further enforced other studies of this nature that drainage basins were dynamic and functional entities whose operations were governed by complex interrelationships occurring within the basins. Changes to any of the geomorphometric properties would influence their role as basin regulators thus influencing a change in basin response. In the case of the basin's minimum low flow, a change in any of the properties considered in the regression model influenced the "time to peak" of flow. A shorter time period would mean higher discharge, which is generally considered the prerequisite to flooding. This research also conclude that the role of geomorphometric properties to control the water supply within the stream through out the year even though during the drought and less precipitations months. Drainage basins are sensitive entities and any deteriorations involve will generate reciprocals and response to the water supply as well as the habitat within the areas.

Matched MeSH terms: Models, Statistical
Fulltext Optimization of thermostable organic solvent-tolerant lipase production by thermotolerant Rhizopus sp. using solid-state fermentation of palm kernel cake

Riyadi FA, Alam MZ, Salleh MN, Salleh HM

3 Biotech, 2017 Oct;7(5):300.
PMID: 28884067 DOI: 10.1007/s13205-017-0932-1

This study enhanced the production of thermostable organic solvent-tolerant (TS-OST) lipase by locally isolated thermotolerant Rhizopus sp. strain using solid-state fermentation (SSF) of palm kernel cake (PKC). The optimum conditions were achieved using a series of statistical approaches. The cultivation parameters, which include fermentation time, moisture content, temperature, pH, inoculum size, various carbon and nitrogen sources, as well as other supplements, were initially screened by the definitive screening design, and one-factor-at-a-time using PKC as the basal medium. Three significant factors (olive oil concentration, pH, and inoculum size) were further optimized using face-centred central composite design. The results indicated a successful and significant improvement of lipase activity by almost two-fold compared to the initial screening production. The findings showed that the optimal conditions were 2% (v/w) inoculum size, 2% (v/w) olive oil, 0.6% (w/w) peptone, 2% (v/w) ethanol, 70% moisture content at initial pH 10.0 and 45 °C within 72 h of fermentation. Process optimization resulted in maximum lipase activity of 58.63 U/gram dry solids (gds). The analysis of variance showed that the statistical model was significant (p value <0.0001) and reliable with a high value of R2 (0.98) and adjusted R2 (0.96). This indicates a better correlation between the actual and predicted responses of lipase production. By considering this study, the low-cost PKC through SSF appears to be promising in the utilization of agro-industrial waste for TS-OST lipase production. This is because satisfactory enzyme activity could be attained that promises industrial applications.

Matched MeSH terms: Models, Statistical
Kinetic behaviour of free lipase and mica-based immobilized lipase catalyzing the synthesis of sugar esters

Zaidan UH, Abdul Rahman MB, Othman SS, Basri M, Abdulmalek E, Rahman RN, et al.

Biosci Biotechnol Biochem, 2011;75(8):1446-50.
PMID: 21821960

The utilization of natural mica as a biocatalyst support in kinetic investigations is first described in this study. The formation of lactose caprate from lactose sugar and capric acid, using free lipase (free-CRL) and lipase immobilized on nanoporous mica (NER-CRL) as a biocatalyst, was evaluated through a kinetic study. The apparent kinetic parameters, K(m) and V(max), were determined by means of the Michaelis-Menten kinetic model. The Ping-Pong Bi-Bi mechanism with single substrate inhibition was adopted as it best explains the experimental findings. The kinetic results show lower K(m) values with NER-CRL than with free-CRL, indicating the higher affinity of NER-CRL towards both substrates at the maximum reaction velocity (V(max,app)>V(max)). The kinetic parameters deduced from this model were used to simulate reaction rate data which were in close agreement with the experimental values.

Matched MeSH terms: Models, Statistical
Fulltext Optimization of physical conditions for the production of thermostable T1 lipase in Pichia guilliermondii strain SO using response surface methodology

Abu ML, Nooh HM, Oslan SN, Salleh AB

BMC Biotechnol, 2017 Nov 10;17(1):78.
PMID: 29126403 DOI: 10.1186/s12896-017-0397-7

BACKGROUND: Pichia guilliermondii was found capable of expressing the recombinant thermostable lipase without methanol under the control of methanol dependent alcohol oxidase 1 promoter (AOXp 1). In this study, statistical approaches were employed for the screening and optimisation of physical conditions for T1 lipase production in P. guilliermondii.
RESULT: The screening of six physical conditions by Plackett-Burman Design has identified pH, inoculum size and incubation time as exerting significant effects on lipase production. These three conditions were further optimised using, Box-Behnken Design of Response Surface Methodology, which predicted an optimum medium comprising pH 6, 24 h incubation time and 2% inoculum size. T1 lipase activity of 2.0 U/mL was produced with a biomass of OD600 23.0.
CONCLUSION: The process of using RSM for optimisation yielded a 3-fold increase of T1 lipase over medium before optimisation. Therefore, this result has proven that T1 lipase can be produced at a higher yield in P. guilliermondii.

Matched MeSH terms: Models, Statistical
The use of response surface methodology for enhanced production of a thermostable bacterial lipase in a novel yeast system

Abu ML, Mohammad R, Oslan SN, Salleh AB

Prep Biochem Biotechnol, 2021;51(4):350-360.
PMID: 32940138 DOI: 10.1080/10826068.2020.1818256

A thermostable bacterial lipase from Geobacillus zalihae was expressed in a novel yeast Pichia sp. strain SO. The preliminary expression was too low and discourages industrial production. This study sought to investigate the optimum conditions for T1 lipase production in Pichia sp. strain SO. Seven medium conditions were investigated and optimized using Response Surface Methodology (RSM). Five responding conditions namely; temperature, inoculum size, incubation time, culture volume and agitation speed observed through Plackett-Burman Design (PBD) method had a significant effect on T1 lipase production. The medium conditions were optimized using Box-Behnken Design (BBD). Investigations reveal that the optimum conditions for T1 lipase production and Biomass concentration (OD600) were; Temperature 31.76 °C, incubation time 39.33 h, culture volume 132.19 mL, inoculum size 3.64%, and agitation speed of 288.2 rpm with a 95% PI low as; 12.41 U/mL and 95% PI high of 13.65 U/mL with an OD600 of; 95% PI low as; 19.62 and 95% PI high as; 22.62 as generated by the software was also validated. These predicted parameters were investigated experimentally and the experimental result for lipase activity observed was 13.72 U/mL with an OD600 of 24.5. At these optimum conditions, there was a 3-fold increase on T1 lipase activity. This study is the first to develop a statistical model for T1 lipase production and biomass concentration in Pichia sp. Strain SO. The optimized production of T1 lipase presents a choice for its industrial application.

Matched MeSH terms: Models, Statistical*
Fulltext Statistical Modelling of the Effects of Weather Factors on Malaria Occurrence in Abuja, Nigeria

Segun OE, Shohaimi S, Nallapan M, Lamidi-Sarumoh AA, Salari N

Int J Environ Res Public Health, 2020 05 16;17(10).
PMID: 32429373 DOI: 10.3390/ijerph17103474

Background: despite the increase in malaria control and elimination efforts, weather patterns and ecological factors continue to serve as important drivers of malaria transmission dynamics. This study examined the statistical relationship between weather variables and malaria incidence in Abuja, Nigeria. Methodology/Principal Findings: monthly data on malaria incidence and weather variables were collected in Abuja from the year 2000 to 2013. The analysis of count outcomes was based on generalized linear models, while Pearson correlation analysis was undertaken at the bivariate level. The results showed more malaria incidence in the months with the highest rainfall recorded (June-August). Based on the negative binomial model, every unit increase in humidity corresponds to about 1.010 (95% confidence interval (CI), 1.005-1.015) times increase in malaria cases while the odds of having malaria decreases by 5.8% for every extra unit increase in temperature: 0.942 (95% CI, 0.928-0.956). At lag 1 month, there was a significant positive effect of rainfall on malaria incidence while at lag 4, temperature and humidity had significant influences. Conclusions: malaria remains a widespread infectious disease among the local subjects in the study area. Relative humidity was identified as one of the factors that influence a malaria epidemic at lag 0 while the biggest significant influence of temperature was observed at lag 4. Therefore, emphasis should be given to vector control activities and to create public health awareness on the proper usage of intervention measures such as indoor residual sprays to reduce the epidemic especially during peak periods with suitable weather conditions.

Matched MeSH terms: Models, Statistical*

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