scholarly journals Geospatial modelling to estimate the territory at risk of establishment of influenza type A in Mexico - An ecological study

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Enrique Ibarra-Zapata ◽  
Darío Gaytán-Hernández ◽  
Verónica Gallegos-García ◽  
Claudia Elena González-Acevedo ◽  
Thuluz Meza-Menchaca ◽  
...  

The aim of this study was to estimate the territory at risk of establishment of influenza type A (EOITA) in Mexico, using geospatial models. A spatial database of 1973 outbreaks of influenza worldwide was used to develop risk models accounting for natural (natural threat), anthropic (man-made) and environmental (combination of the above) transmission. Then, a virus establishment risk model; an introduction model of influenza A developed in another study; and the three models mentioned were utilized using multi-criteria spatial evaluation supported by geographically weighted regression (GWR), receiver operating characteristic analysis and Moran’s I. The results show that environmental risk was concentrated along the Gulf and Pacific coasts, the Yucatan Peninsula and southern Baja California. The identified risk for EOITA in Mexico were: 15.6% and 4.8%, by natural and anthropic risk, respectively, while 18.5% presented simultaneous environmental, natural and anthropic risk. Overall, 28.1% of localities in Mexico presented a High/High risk for the establishment of influenza type A (area under the curve=0.923, P<0.001; GWR, r2=0.840, P<0.001; Moran’s I =0.79, P<0.001). Hence, these geospatial models were able to robustly estimate those areas susceptible to EOITA, where the results obtained show the relation between the geographical area and the different effects on health. The information obtained should help devising and directing strategies leading to efficient prevention and sound administration of both human and financial resources.

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
David Muscatello ◽  
Robert Neil F. Leong ◽  
Robin M. Turner ◽  
Anthony T. Newall

ObjectiveUsing the epidemic of influenza type A in 2016 in Australia, we demonstrated a simple but statistically sound adaptive method of automatically representing the spatial intensity and evolution of an influenza epidemic that could be applied to a laboratory surveillance count data stream that does not have a denominator.IntroductionSurveillance of influenza epidemics is a priority for risk assessment and pandemic preparedness. Mapping epidemics can be challenging because influenza infections are incompletely ascertained, ascertainment can vary spatially, and often a denominator is not available. Rapid, more refined geographic or spatial intelligence could facilitate better preparedness and response.MethodsWeekly counts of persons with laboratory confirmed influenza type A infections in Australia in 2016 were analysed by 86 sub-state geographical areas. Weekly standardised epidemic intensity was represented by a z-score calculated using the standard deviation of below-median counts in the previous 52 weeks. A geographic information system was used to present the epidemic progression.ResultsThere were 79,628 notifications of influenza A infections included. Of these, 79,218 (99.5%) were allocated to a geographical area. The maps indicated areas of elevated epidemic intensity across Australia by week and area, that were consistent with the observed start, peak and decline of the epidemic when compared with weekly counts aggregated at the state and territory level. An example is shown in Figure 1.ConclusionsThe methods could be automated to rapidly generate spatially varying epidemic intensity maps using a surveillance data stream. This could improve local level epidemic intelligence in a variety of settings and for other diseases. It may also increase our understanding of geographic epidemic dynamics. 


2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Xin Wang ◽  
Shisong Fang

ObjectiveTo determine avian influenza A(H5N6) virus infection in humanand environment using extensive surveillances. To evaluate theprevalence of H5N6 infection among high risk population.IntroductionSince the emergence of avian influenza A(H7N9) virus in 2013,extensive surveillances have been established to monitor the humaninfection and environmental contamination with avian influenza virusin southern China. At the end of 2015, human infection with influenzaA(H5N6) virus was identified in Shenzhen for the first time throughthese surveillances. These surveillances include severe pneumoniascreening, influenza like illness (ILI) surveillance, follow-up onclose contact of the confirmed case, serological survey among poultryworkers, environment surveillance in poultry market.MethodsSevere pneumonia screening was carried out in all hospitals ofShenzhen. When a patient with severe pneumonia is suspected forinfection with avian influenza virus, after consultation with at leasttwo senior respiratory physicians from the designated expert paneland gaining their approval, the patient will be reported to local CDC,nasal and pharyngeal swabs will be collected and sent for detectionof H5N6 virus by RT-PCR.ILI surveillance was conducted in 11 sentinel hospitals, 5-20 ILIcases were sampled for detection of seasonal influenza virus by RT-PCR test every week for one sentinel. If swab sample is tested positivefor influenza type A and negative for subtypes of seasonal A(H3N2)and A(H1N1), it will be detected further for influenza A(H5N6) virus.Follow-up on close contacts was immediately carried out whenhuman case of infection with H5N6 was identified. All of closecontacts were requested to report any signs and symptoms of acuterespiratory illness for 10 days, nasal and pharyngeal swabs werecollected and tested for influenza A(H5N6) virus by RT-PCR test.In the meantime, environmental samples were collected in the marketwhich was epidemiologically associated with patient and tested forH5N6 virus by RT-PCR test.Serological survey among poultry workers was conducted in tendistricts of Shenzhen. Poultry workers were recruited in poultrymarkets and screened for any signs and symptoms of acute respiratoryillness, blood samples were collected to detect haemagglutination-inhibition (HI) antibody for influenza A(H5N6) virus.Environment surveillance was conducted twice a month in tendistricts of Shenzhen. For each district, 10 swab samples werecollected at a time. All environmental samples were tested forinfluenza A(H5N6) virus by RT-PCR test.ResultsFrom Nov 1, 2015 to May 31, 2016, 50 patients with severepneumonia were reported and detected for H5N6 virus, three patientswere confirmed to be infected with H5N6 virus. Case 1 was a 26 yearsold woman and identified on Dec 29, 2015. She purchased a duck ata live poultry stall of nearby market, cooked and ate the duck 4 daysbefore symptom onset. After admission to hospital on Dec 27, hercondition deteriorated rapidly, on Dec 30 she died. The case 2 was a25 years old man and confirmed on Jan 7, 2016. He visited a marketeveryday and had no close contact with poultry, except for passingby live poultry stalls. He recovered and was discharged from hospitalon Jan 22. The case 3 was is a 31 years old woman and reported onJan 16, 2016, she had no contact with live poultry and died on Feb 8.For 60 close contacts of three cases, none of them reported signsor symptoms of acute respiratory illness, all of nasal and pharyngealswabs were tested negative for influenza A(H5N6) virus by RT-PCRtest. Of 146 environmental swabs collected in the case’s living placesand relevant poultry markets, 38 were tested positive for influenzaA(H5N6) virus by RT-PCR test.From Nov 1, 2015 to May 31, 2016, 2812 ILI cases were sampledand tested for influenza type A and subtypes of seasonal influenza.Those samples tested positive for influenza type A could be furthersubtyped to seasonal A(H3N2) or A(H1N1), therefore no sample fromILI case was tested for influenza A(H5N6) virus.Serological surveys among poultry workers were conductedtwice, for the first survey 186 poultry workers were recruited in Oct2015, for the second survey 195 poultry workers were recruited inJan 2016. Blood sample were collected and tested for HI antibodyof influenza A(H5N6) virus. 2 individuals had H5N6 HI antibodytiter of 1:40, 5 individuals had H5N6 HI antibody titer of 1:20, rest ofthem had H5N6 HI antibody titer of <1:20. According to the WHOguideline, HI antibody titer of≥1:160 against avian influenza viruswere considered positive.From Nov 1, 2015 to May 31, 2016, of 1234 environmental swabscollected in poultry markets, 339 (27.5%)were tested positive forinfluenza A(H5N6) virus by RT-PCR test. Each of the ten districtshad poultry markets which was contaminated by influenza A(H5N6)virus.ConclusionsIn 2015-2016 winter, three cases of infection with influenzaA(H5N6) virus were identified in Shenzhen, all of them were youngindividuals with average age of 27.3 years and developed severepneumonia soon after illness onset, two cases died. For acute andsevere disease, early detection and treatment is the key measure forpatient’s prognosis.H5N6 virus was identified in poultry market and other placeswhere patient appeared, implying poultry market probably was thesource of infection. Despite the high contamination rate of H5N6virus in poultry market, we found that the infection with H5N6 virusamong poultry workers was not prevalent, with infection rate being0/381. Human infection with H5N6 virus seemed to be a sporadicoccurrence, poultry-human transmission of H5N6 virus might not bevery effective.


2002 ◽  
Vol 41 (03) ◽  
pp. 213-215 ◽  
Author(s):  
H. Sugimori ◽  
K. Yoshida ◽  
M. Suka

Summary Objectives: To examine whether the Framingham Risk Model can appropriately predict coronary heart disease (CHD) events detected by electrocardiography (ECG) in Japanese men. Methods: Using the annual health examination database of a Japanese company 5611 male workers, between the ages of 30 to 59, who were free of cardiovascular disease, were followed up to observe the occurrence of CHD events detected by ECG over a period of five to seven years. The probability of CHD was calculated for each individual from the equations of the Framingham risk model (with total cholesterol). Results: The incidence of CHD increased with the estimated CHD risk. The Hosmer-Lemeshow goodness of fit test showed an adequate fit of the risk model to the data of the study subjects. In the receiver operating characteristic analysis, the area under the curve reached 0.67 which indicated an acceptable discriminatory accuracy of the risk model. Conclusions: The Framingham risk model provides useful information on future CHD events in Japanese men.


2020 ◽  
Vol 13 (9) ◽  
pp. 1966-1969
Author(s):  
Abdelmohsen Abduallah Alnaeem ◽  
Abdulkareem Al-Shabeb ◽  
Maged Gomaa Hemida

Background and Aim: Influenza type A virus infections are still one of the major concerns for the health of humans and various species of domestic and companion animals. Wild birds play an essential role in the transmission cycle of the virus. Regularly monitoring the spread of the virus is a significant step in its mitigation. Highly pathogenic avian influenza viruses, including H5N1 and H5N8, have been reported in birds in the Arabian Peninsula, including Saudi Arabia, in recent decades. This study aimed to evaluate the immune status of birds, domestic and companion animals for Influenza type A virus in Eastern Province of Saudi Arabia. Materials and Methods: We collected 195 serum samples from dromedary camels, sheep, goats, native breed chickens, doves, dogs, and cats. We tested these sera for the presence of specific antibodies against influenza type A virus using a commercially available enzyme-linked immunosorbent assay. Results: Our results show that 4% of the tested samples had antibodies in sera, including some doves, chickens, and dogs. These data suggest exposure and seroconversion of these animals or birds to the influenza type A virus. Conclusion: The presence of antibodies against influenza type A virus in sera of some animals and birds without a previous vaccination history against the virus indicates a natural exposure history regarding this virus and seroconversion. Further large-scale molecular and epidemiological studies are needed to obtain a better understanding of the dynamics of influenza type A virus among various species of animals and birds.


2017 ◽  
Vol 8 (4) ◽  
Author(s):  
Matheus Supriyanto Rumetna ◽  
Eko Sediyono ◽  
Kristoko Dwi Hartomo

Abstract. Bantul Regency is a part of Yogyakarta Special Province Province which experienced land use changes. This research aims to assess the changes of shape and level of land use, to analyze the pattern of land use changes, and to find the appropriateness of RTRW land use in Bantul District in 2011-2015. Analytical methods are employed including Geoprocessing techniques and analysis of patterns of distribution of land use changes with Spatial Autocorrelation (Global Moran's I). The results of this study of land use in 2011, there are thirty one classifications, while in 2015 there are thirty four classifications. The pattern of distribution of land use change shows that land use change in 2011-2015 has a Complete Spatial Randomness pattern. Land use suitability with the direction of area function at RTRW is 24030,406 Ha (46,995406%) and incompatibility of 27103,115 Ha or equal to 53,004593% of the total area of Bantul Regency.Keywords: Geographical Information System, Land Use, Geoprocessing, Global Moran's I, Bantul Regency. Abstrak. Analisis Perubahan Tata Guna Lahan di Kabupaten Bantul Menggunakan Metode Global Moran’s I. Kabupaten Bantul merupakan bagian dari Provinsi Daerah Istimewa Yogyakarta yang mengalami perubahan tata guna lahan. Penelitian ini bertujuan untuk mengkaji perubahan bentuk dan luas penggunaan lahan, menganalisis pola sebaran perubahan tata guna lahan, serta kesesuaian tata guna lahan terhadap RTRW yang terjadi di Kabupaten Bantul pada tahun 2011-2015. Metode analisis yang digunakan antara lain teknik Geoprocessing serta analisis pola sebaran perubahan tata guna lahan dengan Spatial Autocorrelation (Global Moran’s I). Hasil dari penelitian ini adalah penggunaan tanah pada tahun 2011, terdapat tiga puluh satu klasifikasi, sedangkan pada tahun 2015 terdapat tiga puluh empat klasifikasi. Pola sebaran perubahan tata guna lahan menunjukkan bahwa perubahan tata guna lahan tahun 2011-2015 memiliki pola Complete Spatial Randomness. Kesesuaian tata guna lahan dengan arahan fungsi kawasan pada RTRW adalah seluas 24030,406 Ha atau mencapai 46,995406 % dan ketidaksesuaian seluas 27103,115 Ha atau sebesar 53,004593 % dari total luas wilayah Kabupaten Bantul. Kata Kunci: Sistem Informasi Georafis, tata guna lahan, Geoprocessing, Global Moran’s I, Kabupaten Bantul.


2012 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Asra Hosseini

From earliest cities to the present, spatial division into residential zones and neighbourhoods is the universal feature of urban areas. This study explored issue of measuring neighbourhoods through spatial autocorrelation method based on Moran's I index in respect of achieving to best neighbourhoods' model for forming cities smarter. The research carried out by selection of 35 neighbourhoods only within central part of traditional city of Kerman in Iran. The results illustrate, 75% of neighbourhoods' area in the inner city of Kerman had clustered pattern, and it shows reduction in Moran's index is associated with disproportional distribution of density and increasing in Moran's I and Z-score have monotonic relation with more dense areas and clustered pattern. It may be more efficient for urban planner to focus on spatial autocorrelation to foster neighbourhood cohesion rather than emphasis on suburban area. It is recommended characteristics of historic neighbourhoods can be successfully linked to redevelopment plans toward making city smarter, and also people's quality of life can be related to the way that neighbourhoods' patterns are defined. 


2012 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Asra Hosseini

From earliest cities to the present, spatial division into residential zones and neighbourhoods is the universal feature ofurban areas. This study explored issue ofmeasuring neighbourhoods through spatial autocorrelation method based on Moran's I index in respect of achieving to best neighbourhoods' model for forming cities smarter. The research carried out by selection of 35 neighbourhoods only within central part of traditional city of Kerman in Iran. The results illustrate, 75% ofneighbourhoods, area in the inner city of Kerman had clustered pattern, and it shows reduction in Moran's index is associated with disproportional distribution of density and increasing in Moran's I and Z-score have monotonic relation with more dense areas and clustered pattern. It may be more efficient for urban planner to focus on spatial autocorrelation to foster neighbourhood cohesion rather than emphasis on suburban area. It is recommended characteristics of historic neighbourhoods can be successfully linked to redevelopment plans toward making city smarter, and also people's quality of life can be related to the way that neighbourhoods' patterns are defined.


2020 ◽  
Vol 30 (5) ◽  
pp. 746-753
Author(s):  
Ning Dong ◽  
Hulin Piao ◽  
Yu Du ◽  
Bo Li ◽  
Jian Xu ◽  
...  

Abstract OBJECTIVES Acute kidney injury (AKI) is a common complication of cardiovascular surgery that is associated with increased mortality, especially after surgeries involving the aorta. Early detection and prevention of AKI in patients with aortic dissection may help improve outcomes. The objective of this study was to develop a practical prediction score for AKI after surgery for Stanford type A acute aortic dissection (TAAAD). METHODS This was a retrospective cohort study that included 2 independent hospitals. A larger cohort of 326 patients from The Second Hospital of Jilin University was used to identify the risk factors for AKI and to develop a risk score. The derived risk score was externally validated in a separate cohort of 102 patients from the other hospital. RESULTS The scoring system included the following variables: (i) age &gt;45 years; (ii) body mass index &gt;25 kg/m2; (iii) white blood cell count &gt;13.5 × 109/l; and (iv) lowest perioperative haemoglobin &lt;100 g/l, cardiopulmonary bypass duration &gt;150 min and renal malperfusion. On receiver operating characteristic curve analysis, the score predicted AKI with fair accuracy in both the derivation [area under the curve 0.778, 95% confidence interval (CI) 0.726–0.83] and the validation (area under the curve 0.747, 95% CI 0.657–0.838) cohorts. CONCLUSIONS We developed a convenient scoring system to identify patients at high risk of developing AKI after surgery for TAAAD. This scoring system may help identify patients who require more intensive postoperative management and facilitate appropriate interventions to prevent AKI and improve patient outcomes.


2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Mukemil Awol ◽  
Zewdie Aderaw Alemu ◽  
Nurilign Abebe Moges ◽  
Kemal Jemal

Abstract Background In Ethiopia, despite the considerable improvement in immunization coverage, the burden of defaulting from immunization among children is still high with marked variation among regions. However, the geographical variation and contextual factors of defaulting from immunization were poorly understood. Hence, this study aimed to identify the spatial pattern and associated factors of defaulting from immunization. Methods An in-depth analysis of the 2016 Ethiopian Demographic and Health Survey (EDHS 2016) data was used. A total of 1638 children nested in 552 enumeration areas (EAs) were included in the analysis. Global Moran’s I statistic and Bernoulli purely spatial scan statistics were employed to identify geographical patterns and detect spatial clusters of defaulting immunization, respectively. Multilevel logistic regression models were fitted to identify factors associated with defaulting immunization. A p value < 0.05 was used to identify significantly associated factors with defaulting of child immunization. Results A spatial heterogeneity of defaulting from immunization was observed (Global Moran’s I = 0.386379, p value < 0.001), and four significant SaTScan clusters of areas with high defaulting from immunization were detected. The most likely primary SaTScan cluster was seen in the Somali region, and secondary clusters were detected in (Afar, South Nation Nationality of people (SNNP), Oromiya, Amhara, and Gambella) regions. In the final model of the multilevel analysis, individual and community level factors accounted for 56.4% of the variance in the odds of defaulting immunization. Children from mothers who had no formal education (AOR = 4.23; 95% CI: 117, 15.78), and children living in Afar, Oromiya, Somali, SNNP, Gambella, and Harari regions had higher odds of having defaulted immunization from community level. Conclusions A clustered pattern of areas with high default of immunization was observed in Ethiopia. Both the individual and community-level characteristics were statistically significant factors of defaulting immunization. Therefore, the Federal Ethiopian Ministry of Health should prioritize the areas with defaulting of immunization and consider the identified factors for immunization interventions.


BMC Nutrition ◽  
2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Biruk Shalmeno Tusa ◽  
Sewnet Adem Kebede ◽  
Adisu Birhanu Weldesenbet

Abstract Background Anemia is a global public health problem, particularly in developing countries. Assessing the geographic distributions and determinant factors is a key and crucial step in designing targeted prevention and intervention programmes to address anemia. Thus, the current study is aimed to assess the spatial distribution and determinant factors of anemia in Ethiopia among adults aged 15–59. Methods A secondary data analysis was done based on 2016 Ethiopian Demographic and Health Surveys (EDHS). Total weighted samples of 29,140 adults were included. Data processing and analysis were performed using STATA 14; ArcGIS 10.1 and SaTScan 9.6 software. Spatial autocorrelation was checked using Global Moran’s index (Moran’s I). Hotspot analysis was made using Gettis-OrdGi*statistics. Additionally, spatial scan statistics were applied to identify significant primary and secondary cluster of anemia. Mixed effect ordinal logistics were fitted to determine factors associated with the level of anemia. Result The spatial distribution of anemia in Ethiopia among adults age 15–59 was found to be clustered (Global Moran’s I = 0.81, p value <  0.0001). In the multivariable mixed-effectordinal regression analysis; Females [AOR = 1.53; 95% CI: 1.42, 1.66], Never married [AOR = 0.86; 95% CI: 0.77, 0.96], highly educated [AOR = 0.71; 95% CI: 0.60, 0.84], rural residents [AOR = 1.53; 95% CI: 1.23, 1.81], rich wealth status [AOR = 0.77; 95% CI: 0.69, 0.86] and underweight [AOR = 1.15; 1.06, 1.24] were significant predictors of anemia among adults. Conclusions A significant clustering of anemia among adults aged 15–59 were found in Ethiopia and the significant hotspot areas with high cluster anemia were identified in Somalia, Afar, Gambella, Dire Dewa and Harari regions. Besides, sex, marital status, educational level, place of residence, region, wealth index and BMI were significant predictors of anemia. Therefore, effective public health intervention and nutritional education should be designed for the identified hotspot areas and risk groups in order to decrease the incidence of anemia.


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