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      Spatial distribution of 12 class B notifiable infectious diseases in China: A retrospective study

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      PLoS ONE
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          Abstract

          Background

          China is the largest developing country with a relatively developed public health system. To further prevent and eliminate the spread of infectious diseases, China has listed 39 notifiable infectious diseases characterized by wide prevalence or great harm, and classified them into classes A, B, and C, with severity decreasing across classes. Class A diseases have been almost eradicated in China, thus making class B diseases a priority in infectious disease prevention and control. In this retrospective study, we analyze the spatial distribution patterns of 12 class B notifiable infectious diseases that remain active all over China.

          Methods

          Global and local Moran’s I and corresponding graphic tools are adopted to explore and visualize the global and local spatial distribution of the incidence of the selected epidemics, respectively. Inter-correlations of clustering patterns of each pair of diseases and a cumulative summary of the high/low cluster frequency of the provincial units are also provided by means of figures and maps.

          Results

          Of the 12 most commonly notifiable class B infectious diseases, viral hepatitis and tuberculosis show high incidence rates and account for more than half of the reported cases. Almost all the diseases, except pertussis, exhibit positive spatial autocorrelation at the provincial level. All diseases feature varying spatial concentrations. Nevertheless, associations exist between spatial distribution patterns, with some provincial units displaying the same type of cluster features for two or more infectious diseases. Overall, high–low (unit with high incidence surrounded by units with high incidence, the same below) and high–high spatial cluster areas tend to be prevalent in the provincial units located in western and southwest China, whereas low–low and low–high spatial cluster areas abound in provincial units in north and east China.

          Conclusion

          Despite the various distribution patterns of 12 class B notifiable infectious diseases, certain similarities between their spatial distributions are present. Substantial evidence is available to support disease-specific, location-specific, and disease-combined interventions. Regarding provinces that show high–high/high–low patterns of multiple diseases, comprehensive interventions targeting different diseases should be established. As to the adjacent provincial units revealing similar patterns, coordinated actions need to be taken across borders.

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          Most cited references34

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          National survey of drug-resistant tuberculosis in China.

          The available information on the epidemic of drug-resistant tuberculosis in China is based on local or regional surveys. In 2007, we carried out a national survey of drug-resistant tuberculosis in China. We estimated the proportion of tuberculosis cases in China that were resistant to drugs by means of cluster-randomized sampling of tuberculosis cases in the public health system and testing for resistance to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and streptomycin and the second-line drugs ofloxacin and kanamycin. We used the results from this survey and published estimates of the incidence of tuberculosis to estimate the incidence of drug-resistant tuberculosis. Information from patient interviews was used to identify factors linked to drug resistance. Among 3037 patients with new cases of tuberculosis and 892 with previously treated cases, 5.7% (95% confidence interval [CI], 4.5 to 7.0) and 25.6% (95% CI, 21.5 to 29.8), respectively, had multidrug-resistant (MDR) tuberculosis (defined as disease that was resistant to at least isoniazid and rifampin). Among all patients with tuberculosis, approximately 1 of 4 had disease that was resistant to isoniazid, rifampin, or both, and 1 of 10 had MDR tuberculosis. Approximately 8% of the patients with MDR tuberculosis had extensively drug-resistant (XDR) tuberculosis (defined as disease that was resistant to at least isoniazid, rifampin, ofloxacin, and kanamycin). In 2007, there were 110,000 incident cases (95% CI, 97,000 to 130,000) of MDR tuberculosis and 8200 incident cases (95% CI, 7200 to 9700) of XDR tuberculosis. Most cases of MDR and XDR tuberculosis resulted from primary transmission. Patients with multiple previous treatments who had received their last treatment in a tuberculosis hospital had the highest risk of MDR tuberculosis (adjusted odds ratio, 13.3; 95% CI, 3.9 to 46.0). Among 226 previously treated patients with MDR tuberculosis, 43.8% had not completed their last treatment; most had been treated in the hospital system. Among those who had completed treatment, tuberculosis developed again in most of the patients after their treatment in the public health system. China has a serious epidemic of drug-resistant tuberculosis. MDR tuberculosis is linked to inadequate treatment in both the public health system and the hospital system, especially tuberculosis hospitals; however, primary transmission accounts for most cases. (Funded by the Chinese Ministry of Health.).
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            The influential factors of urban PM2.5 concentrations in China: a spatial econometric analysis

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              Caregivers’ treatment-seeking behaviour for children under age five in malaria-endemic areas of rural Myanmar: a cross-sectional study

              Background A community-based malaria intervention was introduced through fixed and mobile clinics in rural Myanmar. This study attempted to identify treatment-seeking behaviour of caregivers for children under five and the determinants of appropriate treatment-seeking behaviour in mobile clinic villages (MV) and non-mobile clinic villages (NMV) in malaria-endemic rural areas in Myanmar. Methods A cross-sectional study was conducted in 23 MV and 25 NMV in Ingapu Township, Myanmar. Appropriate treatment-seeking behaviour was operationally defined as seeking treatment from trained personnel or at a health facility within 24 hours after the onset of fever. Multiple logistic regression analyses were conducted to identify the determinants of appropriate treatment-seeking behaviour. Results Among the 597 participants in both types of villages, 166 (35.3%) caregivers sought appropriate treatment. No significant difference in appropriate treatment-seeking behaviour was found between the two types of villages (adjusted odds ratio (AOR), 0.80; 95% confidence interval (CI), 0.51-1.24). Determinants of behaviour include proximity to public health facilities (AOR, 5.86; 95% CI, 3.43-10.02), knowledge of malaria (AOR, 1.90; 95% CI, 1.14-3.17), malaria prevention behaviour (AOR, 1.76; 95% CI, 1.13-2.76), treatment at home (AOR, 0.26; 95% CI, 0.15-0.45), and treatment and transportation costs (AOR, 0.52; 95% CI, 0.33-0.83). Conclusions Caregivers’ treatment-seeking behaviour was poor for fever cases among children under age five, and did not differ significantly between MV and NMV. It is necessary to educate caregivers, particularly for early treatment seeking and appropriate use of health care options for fever, and catering to their medical needs. These findings can help promote awareness and prevention, and improve the quality of interventions at the community level.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                5 April 2018
                2018
                : 13
                : 4
                : e0195568
                Affiliations
                [1 ] School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, Shaanxi, China
                [2 ] Department of Public Policy, City University of Hong Kong, Hong Kong, China
                The University of Hong Kong, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-8271-2524
                Article
                PONE-D-17-14852
                10.1371/journal.pone.0195568
                5886686
                29621351
                0b0369ba-976f-4bc6-9b9c-b514638dfc6a
                © 2018 Zhu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 17 April 2017
                : 26 March 2018
                Page count
                Figures: 5, Tables: 1, Pages: 17
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Infectious Diseases
                Medicine and Health Sciences
                Infectious Diseases
                Infectious Disease Control
                People and Places
                Geographical Locations
                Asia
                China
                Computer and Information Sciences
                Geoinformatics
                Spatial Autocorrelation
                Earth Sciences
                Geography
                Geoinformatics
                Spatial Autocorrelation
                Medicine and Health Sciences
                Infectious Diseases
                Bacterial Diseases
                Tuberculosis
                Medicine and Health Sciences
                Tropical Diseases
                Tuberculosis
                Medicine and Health Sciences
                Infectious Diseases
                Bacterial Diseases
                Typhoid
                Medicine and Health Sciences
                Epidemiology
                Infectious Disease Epidemiology
                Medicine and Health Sciences
                Infectious Diseases
                Infectious Disease Epidemiology
                Medicine and Health Sciences
                Infectious Diseases
                Viral Diseases
                Measles
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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