Spatio-temporal Epidemiology Research Articles

Descriptive and Time-Series Analysis of Rabies in Different Animal Species in Mexico.

The spatio-temporal epidemiology of rabies has related the influence of environmental factors and anthropogenic changes on the movements of the hematophagous bat Desmodus rotundus. In Mexico, D. rotundus is the main transmitter of the rabies virus for different livestock species, modifying annually the fluctuation of the number of cases of rabies and its dissemination in subtropical areas and regions considered free of the disease. The purpose of this study was to perform a descriptive analysis of the distribution of cases of rabies in Mexico, and to perform a time-series analysis to evaluate stationarity and to predict the number of cases for the following year. A total of 3,469 cases were reported in the period of interest, of which the 89.1% occurred in cattle, 4.3% in horses, 1.5% in sheep, 0.6% in goats, 0.01% in pig, 3.1% in vampire bats, 0.3% in cervids, 0.2% in skunks, 0.1% in insectivorous bats, 0.1% in foxes, 0.1% in buffaloes, and 0.02% in coatis; 0.5% were not identified. The most frequent antigenic variants reported were AgV11, AgV5, and AgV3, associated with D. rotundus. The distribution of cases in bats correlates with the distribution of cases in domestic and wild animals; however, cases were observed in wild species in non-endemic areas of Mexico, like the State of Chihuahua. The additive model used in the time-series analysis showed a seasonal pattern with a peak of cases at the beginning of each year, from January to March. The model showed a good predicting value; the Pearson correlation coefficient R2 was 0.705. The highest probability for the occurrence of rabies cases in the different species estimated by Ordinary Kriging was in the coast of the Gulf of Mexico, involving the states of Tamaulipas, Veracruz, Tabasco, Chiapas, and Yucatan. This study confirms that rabies in domestic and wild species is endemic in tropical and subtropical areas—however, cases have been observed in new geographic areas—and provides useful information to support actions to stop the spread of the rabies virus or the reservoir, and for planning vaccination strategies considering time and place.

A comparative analysis of the epidemiology of influenza and respiratory syncytial virus in Russia, 2013/14 to 2018/19.

BackgroundInfluenza and respiratory syncytial virus (RSV) are among the leading causes of lower respiratory tract infections worldwide. We conducted a comparative analysis of the age distribution and spatiotemporal epidemiology of influenza and RSV in Russia using sentinel surveillance data from 2013-14 to 2018-19 in six cities located in the western, central, and eastern regions of the country.MethodsWe calculated the positivity rate for influenza and RSV (by month, season, and overall) in each city, separately for patients seen at the primary and secondary care level (out-patients medical centres housing GP practices and infectious diseases hospitals, respectively). We compared the age distribution of patients infected with the different influenza virus (sub)types and RSV.ResultsA total of 17 551 respiratory specimens were included: the overall positivity rate was 13.5% for influenza and 4.4% for RSV. The A(H1N1)pdm09, A(H3N2) and B virus (sub)types caused 31.3%, 44.0% and, respectively, 24.7% of all influenza cases. The median age was older among influenza (15 years) than among RSV patients (3 years); differences across influenza virus (sub)types were seen only at the primary care level, with influenza A(H3N2) patients being significantly older than A(H1N1)pdm09 or B influenza patients. The timing of influenza epidemics was similar across cities, with the peak typically occurring in February or March. In contrast, the typical peak timing of RSV epidemics varied largely across cities, and the virus was often detected also in spring and summer months (unlike influenza).ConclusionsInfluenza and RSV epidemiology differed in many regards in Russia, especially in the timing of epidemics and the age distribution of infected subjects. Health policies aimed at containing the burden of diseases of viral respiratory infections in Russia should take these findings into account.

Spatiotemporal epidemiology of Japanese encephalitis cases of Dibrugarh district from 2014 to 2018: A hospital record-based descriptive study

Since 1976, several JE outbreaks have been reported from most of the districts of Assam. The present study aims to conduct a descriptive and spatial analysis to understand the spatiotemporal distribution of JE cases of Dibrugarh district. Spatiotemporal distribution of JE cases from 2014 to 2018 at village level was described in maps using Geographical Information System. Spatial association between JE reporting places in the study area has been analyzed using spatial statistics analytical techniques. Temporal distribution of JE cases from 2014 to 2018 for different variable were described in tables. During the period 2014-2018, incidence rate of JE cases ranged between 2.7/100,000 and 5.9/100,000 population and highest case fatality rate was 18.3% in 2014. Highest numbers of JE cases were reported in the age group 0-10 years. Most of the JE cases were from rural areas (84.2%). There was a seasonal pattern of JE which peaked in July. There were hotspots around Dibrugarh Municipality area, Duliajan oil town, Hatiali gaon, Naharkatiya chah bagicha, Nagaon Dhadumia gaon, and Nahortoli Tea Estate. On the basis of the study, JE hotspots can be identified that would help health authorities to further investigate and identify the factors responsible for its occurrence.

The Spatio-temporal Epidemiology of Asthma Patient Visits in Relation to Meteorological Parameters and Air Pollution Factors as a Result of Seasonal Change in Songkhla Province

Objective: To investigate the demographic characteristics, seasonal variations, effects associated with air pollution, and geographic morbidity of asthma in Songkhla.Material and Methods: This research conducted a time series analysis of secondary data from 1 January, 2013 to 31 December, 2017. The distributed lag non-linear model was employed to analyze associations between air pollutants and daily asthma outpatient visits, and the Bayesian hierarchical modelling was used to map asthma morbidity spatiotemporally.Results: A total of 250,127 asthma diagnoses corresponding to 36,761 patients were found in the medical records. Most asthma outpatients were female (61.1%); males (1-5 years) constituted the majority of individuals during the first peak, while females (40-50 years) predominated the second peak. The trend analysis revealed a seasonal variation in the number of asthma outpatient visits; the highest rates were during the June-December period. The regression coefficient analysis revealed carbon monoxide (CO), nitrogen dioxide (NO2 ), relative humidity, and visibility to have the most significant positive effect on asthma, while the cos (wind direction) had the highest negative effect/impact. Significant associations were found between outpatient gender and age and CO, NO2 , sulfur dioxide, ozone, and particulate matter less than 10 micron. The Hat Yai and Central districts of Songkhla province were identified as morbidity hotspots.Conclusion: The number of asthma-related outpatient visits increased during the rainy season. Asthma affected primarily young boys and middle-aged women in this province, and they constitute the most sensitive group to air pollutants such as CO and NO2 and meteorological conditions like relative humidity and visibility. The highest morbidity rates were found in urbanized habitats.

Spatio-temporal epidemiology of emergency medical requests in a large urban area. A scan-statistic approach.

Pre-hospital care is provided by emergency medical services (EMS) staff, the initial health care providers at the scene of disaster. This study aimed to describe the characteristics of EMS callers and space-time distribution of emergency requests in a large urban area. Descriptive thematic maps of EMS requests were created using an empirical Bayesian smoothing approach. Spatial, temporal and spatio-temporal clustering techniques were applied to EMS data based on Kulldorff scan statistics technique. Almost 225,000 calls were registered in the EMS dispatch centre during the study period. Approximately two-thirds of these calls were associated with an altered level of patient consciousness, and the median response time for rural and urban EMS dispatches was 12.2 and 10.1 minutes, respectively. Spatio-temporal clusters of EMS requests were mostly located in central parts of the city, particularly near the downtown area. However, high-response time clustered areas had a low overlap with these general, spatial clusters. This low convergence shows that some unknown factors, other than EMS requests, influence the high-response times. The findings of this study can help policymakers to better allocate EMS resources and implement tailored interventions to enhance EMS system in urban areas.

Integrating Spatiotemporal Epidemiology, Eco-Phylogenetics, and Distributional Ecology to Assess West Nile Disease Risk in Horses.

Mosquito-borne West Nile virus (WNV) is the causative agent of West Nile disease in humans, horses, and some bird species. Since the initial introduction of WNV to the United States (US), approximately 30,000 horses have been impacted by West Nile neurologic disease and hundreds of additional horses are infected each year. Research describing the drivers of West Nile disease in horses is greatly needed to better anticipate the spatial and temporal extent of disease risk, improve disease surveillance, and alleviate future economic impacts to the equine industry and private horse owners. To help meet this need, we integrated techniques from spatiotemporal epidemiology, eco-phylogenetics, and distributional ecology to assess West Nile disease risk in horses throughout the contiguous US. Our integrated approach considered horse abundance and virus exposure, vector and host distributions, and a variety of extrinsic climatic, socio-economic, and environmental risk factors. Birds are WNV reservoir hosts, and therefore we quantified avian host community dynamics across the continental US to show intra-annual variability in host phylogenetic structure and demonstrate host phylodiversity as a mechanism for virus amplification in time and virus dilution in space. We identified drought as a potential amplifier of virus transmission and demonstrated the importance of accounting for spatial non-stationarity when quantifying interaction between disease risk and meteorological influences such as temperature and precipitation. Our results delineated the timing and location of several areas at high risk of West Nile disease and can be used to prioritize vaccination programs and optimize virus surveillance and monitoring.

The spatiotemporal epidemiology of high pathogenicity avian influenza outbreaks in key ostrich producing areas of South Africa

High pathogenicity avian influenza (HPAI) has become a major focus point worldwide due to its zoonotic potential and economic effects resulting from trade restrictions and high mortality rates in poultry. Key ostrich producing provinces of South Africa have experienced three H5N2 HPAI outbreaks (2004, 2006 and 2011) and one H5N8 HPAI (2017) outbreak over the past two decades.The Klein Karoo region in the Western Cape Province, a province with a largely Mediterranean climate, is the predominant ostrich producing region in the country. Understanding the epidemiology of HPAI in ostrich producing areas is an essential first step in developing effective and efficient control measures. This study investigated the spatiotemporal patterns associated with the 2011 (H5N2) and 2017 (H5N8) HPAI outbreaks in the key ostrich producing areas of South Africa. Six hundred and nine and 340 active ostrich farms/holdings were subjected to surveillance during 2011 and 2017 respectively, with over 70 % of these farms located within five local municipalities of the study area. Forty-two and fifty-one farms were affected in the 2011 and 2017 outbreaks respectively. Both HPAI outbreaks occurred predominantly in areas of high ostrich farm density. However, the temporal occurrence, spatial and directional distributions of the outbreaks were different. The 2011 outbreak occurred earlier in the South African autumn months with a predominantly contiguous and stationary distribution, whilst the 2017 outbreak onset was during the winter with a more expansive multidirectional spatial distribution. Results suggest potential dissimilarities in the important risk factors for introduction and possible mode of spread. The 2011 outbreak pattern resembled an outbreak characterised by point introductions with the risk of introduction possibly being linked to high ostrich farm density and common management and husbandry practices in the ostrich industry. In contrast, the 2017 outbreak appeared to have a more propagating mode of transmission. The findings highlight epidemiological features of HPAI outbreak occurrence within ostrich populations that could be used to inform surveillance and control measures including targeted surveillance within high-risk spatial clusters. The study emphasizes the importance of both; implementation of a multi-pronged approach to HPAI control and the need for constant evaluation of the interaction of the host, environment and agent with each outbreak, in order to strengthen disease control.

Spatiotemporal epidemiology and forecasting of dengue in the state of Punjab, India: Study protocol

Dengue burden in India is a major public health problem. The present study has been designed to understand mechanisms by which routine data generate evidence. Secondary data analysis of routine datasets to understand spatiotemporal epidemiology and forecast dengue will be conducted. Data science approach will be adopted to generate a reproducible framework in the R environment. The lab-confirmed dengue reported by the state health authorities from 01 January 2015 to 31 December 2019 will be included. Multiple climatic variables from satellite imagery, climatic models, vegetation and built-up indices, and sociodemographic variables will be explored as risk factors. Exploratory data analysis followed by statistical analysis and machine learning will be performed. Data analysis will include geospatial information analysis, time series analysis, and spatiotemporal analysis. The study will provide value addition to the existing disease surveillance mechanisms by developing a framework for incorporating multiple routine data sources available in the country.

COVID-19 Potential To Infect 4.44% Indian Population

Background: Quantitative characterisation of any contagious diseases could help in making effective strategy to prevent further spreading of the disease. Despite the rapid research in prevention of spreading COVID-19, yet there is no quantitatively information about spatiotemporal epidemiology and epidemic intensity of COVID-19. Therefore, we aimed to quantitatively characterize spatiotemporal epidemiology and epidemic intensity of COVID-19 in Indian geography by determine it’s infectability rate, efficacy rate, transmission rate and likelihood of total populations to be infected with COVID-19 in India. Method: Novel statistical model was designed to quantitatively characterize spatiotemporal epidemiology and epidemic intensity of COVID-19. A Retrospective Cohort study was carried out online and offline in Indian geography using a COVID-19 transmission questionnaires sheet that comprises five mandatory questions. The collected offline as well as online data was then entered into a Microsoft excel sheet to obtain primary data and secondary data required for the mathematical model to calculate quantitative data of spatiotemporal epidemiology and epidemic intensity of COVID-19 in India geography. Result and Discussion: Total 539 responses were analysed in the current study out of 557 received responses between April-2021 to May-2021. Average reproductive number of secondary cases was found 0.77. Infectability rate of COIVD-19 patient was found 38.11% while healthy person has 21.08% risk of becoming infected if they expose to the Primary case. J-Index and H-Index were found 55.32% and 4.44%, respectively, indicating that COVID-19 disease outbreaks as severe epidemic disease in India and has potential to infect ~4.44% Indian population. Conclusion: Higher infectability rate (38.11%) of COIVD-19 patient and higher efficacy rate (21.08%) of healthy individual to be infected with COVID-19 outbreak it a severe epidemic in India. COVID-19 potential to infect about 4.44% India

Spatio-temporal Epidemiology of Malaria Mortality in Nigeria: Why the war against poverty must be won

Malaria is a major parasitic disease in the world including Nigeria which currently bears the brunt of the global malaria mortality burden. This paper responds to the need for all countries in the world including Nigeria to understand the geographical distribution and drivers of malaria mortality with the aim of consolidating the gains of global malaria elimination. The thrust of this paper therefore was to examine the geographical distribution, spatial clustering and determinant(s) of malaria mortality in Nigeria from 2006 to 2010. Retrospective data used in this research were obtained from published sources and were analysed with the aid of statistical and spatial analytical tools. Very noticeable state variations were observed in the pattern of malaria mortality, and strong and persistent clustering of malaria-related deaths was found in northwest Nigeria particularly Kano State due to high levels of malaria transmission. Lastly, there was a significant and differential effect of poverty on its geographical distribution; with the greatest effect felt in the north of Nigeria. In order to reduce death toll associated with the disease, the war against poverty must not only be intensified but should be mainstreamed into the national malaria control programme.

Monitoring the spatiotemporal epidemiology of Covid-19 incidence and mortality: A small-area analysis in Germany

Timely monitoring of incidence risks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and associated deaths at small-area level is essential to inform containment strategies. We analysed the spatiotemporal epidemiology of the SARSCoV- 2 pandemic at district level in Germany to develop a tool for disease monitoring. We used a Bayesian spatiotemporal model to estimate the district-specific risk ratios (RR) of SARS-CoV-2 incidence and the posterior probability (PP) for exceedance of RR thresholds 1, 2 or 3. Of 220 districts (55% of 401 districts) showing a RR > 1, 188 (47%) exceed the RR threshold with sufficient certainty (PP ≥ 80%) to be considered at high risk. 47 districts show very high (RR > 2, PP ≥ 80%) and 15 extremely high (RR > 3, PP ≥ 80%) risks. The spatial approach for monitoring the risk of SARS-CoV-2 provides an informative basis for local policy planning.

Women\u2019s cancers in China: a spatio-temporal epidemiology analysis

BackgroundWomen's cancers, represented by breast and gynecologic cancers, are emerging as a significant threat to women's health, while previous studies paid little attention to the spatial distribution of women's cancers. This study aims to conduct a spatio-temporal epidemiology analysis on breast, cervical and ovarian cancers in China, thus visualizing and comparing their epidemiologic trends and spatio-temporal changing patterns.MethodsData on the incidence and mortality of women’s cancers between January 2010 and December 2015 were obtained from the National Cancer Registry Annual Report. Linear tests and bar charts were used to visualize and compare the epidemiologic trends. Two complementary spatial statistics (Moran’s I statistics and Kulldorff’s space–time scan statistics) were adopted to identify the spatial–temporal clusters.ResultsThe results showed that the incidence and mortality of breast cancer displayed slow upward trends, while that of cervical cancer increase dramatically, and the mortality of ovarian cancer also showed a fast increasing trend. Significant differences were detected in incidence and mortality of breast, cervical and ovarian cancer across east, central and west China. The average incidence of breast cancer displayed a high-high cluster feature in part of north and east China, and the opposite traits occurred in southwest China. In the meantime, the average incidence and mortality of cervical cancer in central China revealed a high-high cluster feature, and that of ovarian cancer in northern China displayed a high-high cluster feature. Besides, the anomalous clusters were also detected based on the space–time scan statistics.ConclusionRegional differences were detected in the distribution of women’s cancers in China. An effective response requires a package of coordinated actions that vary across localities regarding the spatio-temporal epidemics and local conditions.

Regional and gender-specific analyses give new perspectives for secular trend in hip fracture incidence

SummaryIn this study, we found that regional disparity in incidence of hip fractures has converged. Also, annual hip fracture risk ratios between genders have systematically diminished over time.IntroductionSeveral studies have reported secular trends in hip fracture incidence, but knowledge about the possible causes is limited. We studied potential explanations by examining spatio-temporal epidemiology of the fractures and estimating relative risks between genders.MethodsThis observational study was based on all inpatient hospital discharges in 1972–2018 in Finland. We divided the data by gender, 5-year age groups and Finnish sub-regions and estimated gender and age standardized spatio-temporal rates of hip fractures by using a Bayesian age-period-cohort model.ResultsIn 1972, women’s hip fracture incidence was 1.2–1.3 times higher in western and coastal Finland compared to eastern and inland areas. Also, women had approximately 1.7 times higher average risk to get a hip fracture compared to men. Today, the hip fracture differences between the areas have converged to insignificant and the relative risk between genders has diminished to 1.2. Age-specific relative risks indicate greater hip fracture risk for younger men and older women, and the women’s risk increases beyond the risk of men at age 65 which is ten years later than in the beginning of the study period.ConclusionIncidence of hip fracture has converged significantly between regions and genders. Especially factors related with socioeconomic development and increased frailty and longevity seem to be important. The hip fracture incidence rate ratio between women and men has systematically decreased in time, and more attention should be paid to hip fracture risk in men in the future.

Randomly amplified polymorphic DNA analysis of Staphylococcus chromogenes isolated from bovine and bubaline mastitis in Karnataka.

Background and Aim:In recent times, non-aureus staphylococci (NAS) have emerged as the major organisms isolated from mastitis cases in dairy animals, with a predominance of Staphylococcus epidermidis and Staphylococcus chromogenes. As compared to Staphylococcus aureus, much less is known about the molecular types or the spatiotemporal epidemiology of these NAS species. In the present study, randomly amplified polymorphic DNA (RAPD) was employed to detect genetic polymorphisms, intraspecies diversity, and epidemiology of S. chromogenes strains (n=37) isolated from bovine and bubaline mastitis cases in the state of Karnataka.Materials and Methods:Thirty-seven S. chromogenes isolates (14 from bovines and 23 from bubaline) isolated from subclinical mastitis cases, from organized and unorganized sectors, were subjected to RAPD typing. Further, methicillin resistance was determined by cefoxitin disk diffusion method.Results:The amplified DNA fragments ranged from 150 to 3000 base pairs and yielded several RAPD profiles. Further analysis using Digital Image Correlation Engine correlation coefficient and UPGMA method showed that the 37 isolates could be classified into 12 distinct RAPD types (A to L) at 62% similarity (D=0.889). Four of the most predominant RAPD types, B, A, C, and E, in that order, and together, represented 65% of the isolates. High diversity was observed among the isolates both within farms and between geographic locations. Most of the isolates exhibited methicillin resistance. This is the first such report from India.Conclusion:In the absence of defined multilocus sequence type protocols or sufficient sequences available in the public domain, RAPD can be employed to determine genetic diversity of S. chromogenes isolates.

Investigation of tigecycline resistant Escherichia coli from raw meat reveals potential transmission among food-producing animals

To investigate the characteristics of tet(X4)-carrying E. coli from retail raw meat, three hundred and eleven retail raw meat samples including chicken, pork, duck, and beef were collected for screening for tigecycline resistant isolates in Sichuan Province, China. We detected 25 (8.0%, 95%CI: 5.3%–11.6%) tet(X4) positive E. coli isolates from 311 retail meat with the highest prevalence (13.4%, 95%CI: 7.3%–21.8%) observed in pork. All the tet(X)-carrying isolates were analyzed by antimicrobial susceptibility testing, S1 nuclease pulsed-field gel electrophoresis (S1-PFGE), conjugation experiments, and whole genome sequencing (WGS) to study the phylogenetic relationship and genomic characteristics. Conjugation and S1-PFGE profiling showed 6 isolates (24.0%) successfully transferred the resistant phenotype with frequencies from 3.63 × 10−5 to 7.68 × 10−2. Simultaneously, tet(X4), floR, and the characteristic structure of adjacent abh gene and cassette flanked by ISCR2 were identified in all 25 isolates, and a structure of abh-tet(X4)-ISCR2-virD2-floR was aligned as an important genetic pattern around tet(X4). Two dominant sequence types (STs) ST1638 (n = 4) and ST48 (n = 4) were identified by in silico MLST. Single nucleotide polymorphisms analysis revealed two potential clone-like transmission clusters which showed high concordance with the local spatio-temporal epidemiology, suggesting that clonal transmission events were very likely. The presence of tet(X4) in multiple different clone complexes (CCs) and the identification of two clone-like transmission indicates its potentially extensive and successful spread among different food-producing animals.

Analysis of the Global Situation of COVID-19 Research Based on Bibliometrics

Background: With the rapid worldwide spread of the COVID-19 pandemic, researchers have contributed several important advancements. The WHO and countries with severe outbreaks have developed Diagnosis and Treatment Guidelines. Here, we analyze the current transformation and application of scientific research to global epidemic prevention and control. Methods: With a bibliometric clustering algorithm, we described and analyzed current COVID-19 research from the perspectives of international cooperation, interdisciplinary cooperation, and research hotspots. Using the Diagnosis and Treatment Guidelines of the WHO, the United States and China as examples, we assess and compare diagnosis and treatment methods and evaluate the transformation of scientific results from basic research to application. Scientific research results not yet incorporated into these guide lines are summarized to encourage updating and improvement by applying scientific research to prevention and control. Findings: COVID-19 research has fostered interdisciplinary cooperative research, and the current results are mainly concentrated on virus origin, epidemiological characteristics, clinical research, and diagnosis and treatment methods. These results provide strong support for treatment plan formulation. Due to the ongoing publication of new research, Diagnosis and Treatment Guidelines are constantly improving. Comparison of the medical guidelines from the WHO, the United States, and China shows common references and different emphases. Some of the contents lack scientific support, research gaps remain, and some results have not yet been incorporated into the guidelines. Interpretation: The current research is still in the preliminary exploration stage, and there are some problems, such as weak international cooperation, unbalanced interdisciplinary cooperation, and lack of coordination between research and application. Therefore, countries around the world need to improve the International Public Health Emergency Management System and prepare for major public health emergencies in the future. Funding Statement: This work was supported by the China Postdoctoral Science Foundation (No. 2019M662373), The Spatiotemporal Epidemiology of COVID-19 (No.2020SFXGFY02-2). Declaration of Interests: The authors declare no competing interests.

Spatiotemporal Epidemiology of Varicella in Chongqing, China, 2014–2018

Although immunization against varicella using vaccines has been proven to be significant and effective in the past decades, varicella remains a major public health concern for many developing countries. Varicella vaccination has not been introduced into routine immunization programs in China, and varicella outbreaks have continued to occur. Taking the city of Chongqing, which has a high prevalence of varicella, as an example, this study explored the spatiotemporal epidemiology of varicella. Based on the reported data of varicella cases from 1 January 2014 to 31 December 2018 in Chongqing, hot spots and space-time clusters of varicella were identified using spatial autocorrelation analysis and scan statistics. Within this period, a total of 112,273 varicella cases were reported in Chongqing (average annual incidence: 73.44 per 100,000), including one death. The incidence of varicella showed an increasing trend with significant seasonal peaks, which occurred during April to July and October to January of the following year. The total ratio of male to female patients affected was 1.10:1. Children under the age of 15 and students accounted for the majority of the patient population. The hotspots detected through local spatial autocorrelation analysis, and the most likely clusters identified by scan analysis, were primarily in the main urban districts of Chongqing. The secondary clusters were mostly detected in northeast and southwest Chongqing. There were obvious spatial dependence and spatiotemporal clustering characteristics of varicella in Chongqing from 2014 to 2018. High-risk districts, populations, and peak periods were found in this study, which could be helpful in implementing varicella prevention and control programs, and in adjusting vaccination strategies for the varicella vaccine based on actual conditions.

Screening of immunoglobulin g antibodies against chikungunya virus among urban population in Ilorin Nigeria

Chikungunya virus (CHIKV) is a mosquito-borne viral disease which is becoming a serious global public health problem. The principal vector in many parts of Africa is Aedes species . There are recent reports of CHIKV importation into Europe, Asia and America by travelers returning from west and central Africa. Yet, there is scanty information from the guinea savannah region of Nigeria. This study determined previous exposure to CHIKV in the urban population. It is a cross-sectional study involving 89 participants enrolled from three hospitals in Ilorin, Kwara State. A qualitative Chikungunya Enzyme Linked Immunoassay kit was used to detect IgG antibodies. Data was analyzed using SPSS version 22. Statistically significant level was p≤0.05. Out of the study participants, 24.7% were previously exposed to CHIKV. Age group 31-40years had highest proportion while children under 10years had least IgG level. In this study, we found Chikungunya to be endemic in Ilorin Nigeria. There is need for sustained surveillance, to determine spatio-temporal epidemiology of CHIKV. Efforts should be poised to strengthen vector control measures. Keywords: Chikungunya virus, Immunoglobulin G, Guinea Savannah, Ilorin, Urban

Molecular characterization of carbapenem-resistant Acinetobacter baumannii using WGS revealed missed transmission events in Germany from 2012-15.

Infection and colonization with multi-resistant Acinetobacter baumannii causes therapeutic and economic problems in the nosocomial setting. Due to the sensitivity issue of screening schemes for A. baumannii, it is difficult to implement adequate transmission prevention measures. The high discriminatory power of WGS for transmission-chain analysis provides us with the necessary tool to study and identify transmission events. We retrospectively sequenced and analysed 39 A. baumannii isolates from 2012-15 to search for possible missed transmission events. Molecular typing by WGS was performed for non-repetitive (n=39) carbapenem-resistant A. baumannii. Retrospective assessment of patient records was performed to investigate and confirm possible transmission events. Between July 2012 and September 2015, A. baumannii was isolated from 268 patients, of which 16% (42/268) were carbapenem resistant. Thirty-nine of these isolates were recoverable and sequenced. Fifteen percent (6/39) of these were resistant to all antibiotics tested. Most isolates belong to the circulating IC2 clonal type. SNP analysis revealed four potential outbreak clusters. Two of these clusters showed high concordance with the local spatio-temporal epidemiology, suggesting that transmission events were very likely. Our data suggest that there were two independent transmission events, which would have been missed by conventional MLST owing to high clonality. The routine implementation of WGS can optimize surveillance and initiation of suitable containment measures. In addition, emerging resistance to salvage therapy is a major therapeutic problem and should be monitored closely.

Spatiotemporal epidemiology of, and factors associated with, the tuberculosis prevalence in northern China, 2010\u20132014

BackgroundTuberculosis (TB) is an important public health issue worldwide. However, evidence concerning the impact of environmental factors on TB is sparse. We performed a retrospective analysis to determine the spatiotemporal trends and geographic variations of, and the factors associated with, the TB prevalence in Inner Mongolia.MethodsWe performed a retrospective analysis of the epidemiology of TB. A Bayesian spatiotemporal model was used to investigate the spatiotemporal distribution and trends of the TB prevalence. A spatial panel data model was used to identify factors associated with the TB prevalence in the 101 counties of Inner Mongolia, using county-level aggregated data collected by the Inner Mongolia Center for Disease Control and Prevention.ResultsFrom January 2010 to December 2014, 79,466 (6.36‱) incident TB cases were recorded. The TB prevalence ranged from 4.97‱ (12,515/25,167,547) in 2014 to 7.49‱ (18,406/ 24,578,678) in 2010; the majority of TB cases were in males, and in those aged 46–60 years; by occupation, farmers and herdsmen were the most frequently affected. The Bayesian spatiotemporal model showed that the overall TB prevalence decreased linearly from 2010 to 2014 and occupation-stratified analyses yielded similar results, corroborating the reliability of the findings. The decrease of TB prevalence in the central-western and eastern regions was more rapid than that in the overall TB prevalence. A spatial correlation analysis showed spatial clustering of the TB prevalence from 2011 to 2014 (Moran’s index > 0, P < 0.05); in the spatial panel data model, rural residence, birth rate, number of beds, population density, precipitation, air pressure, and sunshine duration were associated with the TB prevalence.ConclusionsThe overall TB prevalence in Inner Mongolia decreased from 2010 to 2014; however, the incidence of TB was high throughout this period. The TB prevalence was influenced by a spatiotemporal interaction effect and was associated with epidemiological, healthcare, and environmental factors.