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1.
Epidemiol Infect ; 147: e77, 2019 01.
Article in English | MEDLINE | ID: mdl-30869010

ABSTRACT

Our objective was to determine the frequency of zika (ZIKV), chikungunya (CHIKV) and dengue (DENV) virus coinfection and describe the mortality cases that occurred during the epidemiologic surveillance of the ZIKV epidemic in Colombia. We analysed all cases of suspected ZIKV infection that were reported to the National Institute of Health (October 2015-December 2016). DENV, CHIKV and ZIKV RNA were detected in serum or tissue samples using polymerase chain reaction assay. Medical records of the fatal cases were reviewed. We identified that 23 871 samples were processed. The frequency of viral agents was 439 (1.84%) for DENV, 257 (1.07%) for CHIKV and 10118 (42.38%) for ZIKV. Thirty-four (0.14%) cases of coinfection were identified. The CHIKV-ZIKV coinfection was present in 28 cases (82.3%), DENV-CHIKV in three (8.8%) and DENV-ZIKV in three (8.8%). Seven (20.6%) coinfection cases were fatal (two DENV-CHIKV cases and five CHIKV-ZIKV cases). Two cases were foetal deaths and the others were related to neurological syndrome and sepsis. In conclusion, the frequency of arbovirus coinfection during epidemic of ZIKV was low, and CHIKV-ZIKV coinfection was the most common. Mortality was high among coinfection patients. The role of each virus in the mortality cases of coinfection warrants further studies.


Subject(s)
Chikungunya Fever/epidemiology , Coinfection/epidemiology , Dengue/epidemiology , Epidemics , Zika Virus Infection/epidemiology , Chikungunya Fever/virology , Chikungunya virus/isolation & purification , Coinfection/virology , Colombia/epidemiology , Dengue/virology , Dengue Virus/isolation & purification , Epidemiological Monitoring , Zika Virus/isolation & purification , Zika Virus Infection/virology
2.
Traffic Inj Prev ; 13 Suppl 1: 5-10, 2012.
Article in English | MEDLINE | ID: mdl-22414122

ABSTRACT

INTRODUCTION: We present a novel multistep technique to estimate the actual burden of road traffic mortality in Mexico during the time period 1999 to 2009 by comparing 3 approaches for redistribution of nonspecific ("garbage") International Classification of Diseases (ICD)-coded deaths. METHODS: Road traffic (RT) mortality data were extracted using a secondary analysis of the Mexican mortality databases for the period 1999 to 2009. In an attempt to correct for underestimation due to inappropriately coded deaths, those deaths assigned to nonspecific codes were redistributed utilizing 3 different adjustment methods. A comparison of the 3 adjustment approaches (proportional, multiple imputation, and regression) is presented. A Poisson regression analysis was utilized to model mortality trends in the raw data and the 3 estimates. RESULTS: After adjustments, the total number of RT deaths increased by 18 to 45 percent, showing significant underestimation when only the raw data are used. All 3 approaches showed statistically significantly higher RT mortality rates than the crude figures. The proportional approach resulted in the highest RT mortality rate estimate of 23 per 100,000 in 2009 and showed a statistically significant positive increase of 1.5 percent per year across the decade. The 60+ age group and pedestrians had the highest mortality rates of 40 and 10.3 per 100,000, respectively. Over the decade, there was an alarming 332 percent increase in the mortality rate for male motorcyclists. CONCLUSION: Though efforts to improve coding should continue to be implemented, we present an additional and often overlooked contribution to the underestimation of road traffic mortality: the ICD nonspecific codes. Improved estimates of road traffic mortality are important in Mexico for policy change and decision making, highlighting the importance of targeting road traffic deaths as a public health problem. The approach presented here may also be useful for estimating the burden of other deaths with similar coding problems.


Subject(s)
Accidents, Traffic/mortality , Databases, Factual/standards , Accidents, Traffic/statistics & numerical data , Adolescent , Adult , Age Distribution , Child , Data Interpretation, Statistical , Female , Humans , International Classification of Diseases , Male , Mexico/epidemiology , Middle Aged , Motorcycles/statistics & numerical data , Sex Distribution , Young Adult
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