Influenza seasonality goes south in the Yucatan Peninsula: The case for a different influenza vaccine calendar in this Mexican region

Influenza in Yucatan in 2018: Chronology, characteristics and outcomes of ambulatory and hospitalized patients

Introduction

Influenza season is expected between October and February in the northern hemisphere, including Mexico. Previous studies suggested that transmission peak may occur earlier in Yucatan, a state in southeast Mexico.

Objectives

(a) Describe the seasonality of 2018 influenza cases seen at O´Horan hospital, statewide, and nationwide; (b) analyze the characteristics, clinical manifestations and outcomes of ambulatory and hospitalized patients; (c) analyze fatal outcomes occurrence among vaccinated and unvaccinated individuals.

Methods

Retrospective analytic cohort of all confirmed influenza cases assisted at O´Horan hospital during 2018, along with a chronologic graphic description of the statewide epidemic curve from the epidemiological surveillance registries.

Results

A total of 264 influenza cases were analyzed; 145 (55%) were female; 26% were vaccinated. Health workers and unvaccinated individuals were more prone to develop severe cases. Dyspnea and tachypnea were strong predictors of hospitalization; headache, myalgias, arthralgias and rhinorrhea correlated inversely. 236 (89.47%) cases occurred in July and 22 of the 23 deaths occurred before October. No fatal outcomes were observed among vaccinated individuals. Influenza AH1N1 represented 83.6% of serotyped cases.

Discussion

Onset of influenza season in Yucatan may reflect a need for rethinking timing of vaccination and of preventive campaigns, as most cases occurred before vaccination period.

Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building

Due to a combination of ecological, political, and demographic factors, the emergence of novel pathogens has been increasingly observed in animals and humans in recent decades. Enhancing global capacity to study and interpret infectious disease surveillance data, and to develop data-driven computational models to guide policy, represents one of the most cost-effective, and yet overlooked, ways to prepare for the next pandemic. Epidemiological and behavioral data from recent pandemics and historic scourges have provided rich opportunities for validation of computational models, while new sequencing technologies and the 'big data' revolution present new tools for studying the epidemiology of outbreaks in real time. For the past two decades, the Division of International Epidemiology and Population Studies (DIEPS) of the NIH Fogarty International Center has spearheaded two synergistic programs to better understand and devise control strategies for global infectious disease threats. The Multinational Influenza Seasonal Mortality Study (MISMS) has strengthened global capacity to study the epidemiology and evolutionary dynamics of influenza viruses in 80 countries by organizing international research activities and training workshops. The Research and Policy in Infectious Disease Dynamics (RAPIDD) program and its precursor activities has established a network of global experts in infectious disease modeling operating at the research-policy interface, with collaborators in 78 countries. These activities have provided evidence-based recommendations for disease control, including during large-scale outbreaks of pandemic influenza, Ebola and Zika virus. Together, these programs have coordinated international collaborative networks to advance the study of emerging disease threats and the field of computational epidemic modeling. A global community of researchers and policy-makers have used the tools and trainings developed by these programs to interpret infectious disease patterns in their countries, understand modeling concepts, and inform control policies. Here we reflect on the scientific achievements and lessons learnt from these programs (h-index = 106 for RAPIDD and 79 for MISMS), including the identification of outstanding researchers and fellows; funding flexibility for timely research workshops and working groups (particularly relative to more traditional investigator-based grant programs); emphasis on group activities such as large-scale modeling reviews, model comparisons, forecasting challenges and special journal issues; strong quality control with a light touch on outputs; and prominence of training, data-sharing, and joint publications.

Temporal distribution and genetic variants in influenza A(H1N1)pdm09 virus circulating in Mexico, seasons 2012 and 2013

The 2012 and 2013 annual influenza epidemics in Mexico were characterized by presenting different seasonal patterns. In 2012 the A(H1N1)pdm09 virus caused a high incidence of influenza infections after a two-year period of low circulation; whereas the 2013 epidemic presented circulation of the A(H1N1)pdm09 virus throughout the year. We have characterized the molecular composition of the Hemagglutinin (HA) and Neuraminidase (NA) genes of the A(H1N1)pdm09 virus from both epidemic seasons, emphasizing the genetic characteristics of viruses isolated from Yucatan in Southern Mexico. The molecular analysis of viruses from the 2012 revealed that all viruses from Mexico were predominantly grouped in clade 7. Strikingly, the molecular characterization of viruses from 2013 revealed that viruses circulating in Yucatan were genetically different to viruses from other regions of Mexico. In fact, we identified the occurrence of two genetic variants containing relevant mutations at both the HA and NA surface antigens. There was a difference on the temporal circulation of each genetic variant, viruses containing the mutations HA-A141T / NA-N341S were detected in May, June and July; whereas viruses containing the mutations HA-S162I / NA-L206S circulated in August and September. We discuss the significance of these novel genetic changes.