Seroprevalence of Protective Antibodies Against Influenza and the Reduction of the Influenza Incidence Rate: An Annual Repeated Cross-Sectional Study From 2014 to 2019.

BACKGROUND: Seroepidemiological studies provide estimates of population-level immunity, prevalence/incidence of infections, and evaluation of vaccination programs. We assessed the seroprevalence of protective antibodies against influenza and evaluated the correlation of seroprevalence with the cumulative annual influenza incidence rate. METHODS: We conducted an annual repeated cross-sectional seroepidemiological survey, during June-August, from 2014 to 2019, in Portugal. A total of 4326 sera from all age groups, sex, and regions was tested by hemagglutination inhibition assay. Seroprevalence and geometric mean titers (GMT) of protective antibodies against influenza were assessed by age group, sex, and vaccine status (65+ years old). The association between summer annual seroprevalence and the difference of influenza incidence rates between one season and the previous one was measured by Pearson correlation coefficient (r). RESULTS: Significant differences in seroprevalence of protective antibodies against influenza were observed in the population. Higher seroprevalence and GMT for A(H1N1)pdm09 and A(H3N2) were observed in children (5-14); influenza B seroprevalence in adults 65+ was 1.6-4.4 times than in children (0-4). Vaccinated participants (65+) showed significant higher seroprevalence/GMT for influenza. A strong negative and significant correlation was found between seroprevalence and ILI incidence rate for A(H1N1)pdm09 in children between 5 and 14 (r = -0.84; 95% CI, -0.98 to -0.07); a weak negative correlation was observed for A(H3N2) and B/Yamagata (r ≤ -0.1). CONCLUSIONS: The study provides new insight into the anti-influenza antibodies seroprevalence measured in summer on the ILI incidence rate in the next season and the need for adjusted preventive health care measures to prevent influenza infection and transmission.

Cross-protection to new drifted influenza A(H3) viruses and prevalence of protective antibodies to seasonal influenza, during 2014 in Portugal.

INTRODUCTION: Immune profile for influenza viruses is highly changeable over time. Serological studies can assess the prevalence of influenza, estimate the risk of infection, highlight asymptomatic infection rate and can also provide data on vaccine coverage. The aims of the study were to evaluate pre-existing cross-protection against influenza A(H3) drift viruses and to assess influenza immunity in the Portuguese population. MATERIALS AND METHODS: We developed a cross-sectional study based on a convenience sample of 626 sera collected during June 2014, covering all age groups, both gender and all administrative health regions of Portugal. Sera antibody titers for seasonal and new A(H3) drift influenza virus were evaluated by hemagglutination inhibition assay (HI). Seroprevalence to each seasonal influenza vaccine strain virus and to the new A(H3) drift circulating strain was estimated by age group, gender and region and compared with seasonal influenza-like illness (ILI) incidence rates before and after the study period. RESULTS: Our findings suggest that seroprevalences of influenza A(H3) (39.9%; 95% CI: 36.2-43.8) and A(H1)pdm09 (29.7%; 95% CI: 26.3-33.4) antibodies were higher than for influenza B, in line with high ILI incidence rates for A(H3) followed by A(H1)pdm09, during 2013/2014 season. Low pre-existing cross-protection against new A(H3) drift viruses were observed in A(H3) seropositive individuals (46%). Both against influenza A(H1)pdm09 and A(H3) seroprotection was highest in younger than 14-years old. Protective antibodies against influenza B were highest in those older than 65years old, especially for B/Yamagata lineage, 33.3% (95% CI: 25.7-41.9). Women showed a high seroprevalence to influenza, although without statistical significance, when compared to men. A significant decreasing trend in seroprotection from north to south regions of Portugal mainland was observed. CONCLUSIONS: Our results emphasize that low seroprotection increases the risk of influenza infection in the following winter season. Seroepidemiological studies can inform policy makers on the need for vaccination and additional preventive measures.

An Integrated Soft Computing Approach to Hughes Syndrome Risk Assessment.

The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestations. This autoimmune hypercoagulable state, usually known as Hughes syndrome, has severe consequences for the patients, being one of the main causes of thrombotic disorders and death. Therefore, it is required to be preventive; being aware of how probable is to have that kind of syndrome. Despite the updated of antiphospholipid syndrome classification, the diagnosis remains difficult to establish. Additional research on clinically relevant antibodies and standardization of their quantification are required in order to improve the antiphospholipid syndrome risk assessment. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model allows for improving the diagnosis, classifying properly the patients that really presented this pathology (sensitivity higher than 85%), as well as classifying the absence of APS (specificity close to 95%).

A case-based reasoning view of thrombophilia risk.

Thrombophilia stands for a genetic or an acquired tendency to hypercoagulable states that increase the risk of venous and arterial thromboses. Indeed, venous thromboembolism is often a chronic illness, mainly in deep venous thrombosis and pulmonary embolism, requiring lifelong prevention strategies. Therefore, it is crucial to identify the cause of the disease, the most appropriate treatment, the length of treatment or prevent a thrombotic recurrence. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a logic programming approach to knowledge representation and reasoning, complemented with a case-based approach to computing. The proposed model has been quite accurate in the assessment of thrombophilia predisposition risk, since the overall accuracy is higher than 90% and sensitivity ranging in the interval [86.5%, 88.1%]. The main strength of the proposed solution is the ability to deal explicitly with incomplete, unknown, or even self-contradictory information.