INFLUENZA CONFERENCE


Influenza Conference is one of the leading research topics in the international research conference domain. Influenza is a conference track under the Healthcare Conference which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Healthcare.

internationalconference.net provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of (Healthcare).

Influenza is not just a call for academic papers on the topic; it can also include a conference, event, symposium, scientific meeting, academic, or workshop.

You are welcome to SUBMIT your research paper or manuscript to Influenza Conference Track will be held at .

Influenza is also a leading research topic on Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, Elsevier, Scopus, Web of Science.

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I. INTERNATIONAL HEALTHCARE CONFERENCE

MARCH 19 - 20, 2019
ISTANBUL, TURKEY

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II. INTERNATIONAL HEALTHCARE CONFERENCE

JUNE 26 - 27, 2019
PARIS, FRANCE

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III. INTERNATIONAL HEALTHCARE CONFERENCE

AUGUST 21 - 22, 2019
LONDON, UNITED KINGDOM

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IV. INTERNATIONAL HEALTHCARE CONFERENCE

OCTOBER 08 - 09, 2019
NEW YORK, UNITED STATES

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V. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 12 - 13, 2019
ROME, ITALY

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VI. INTERNATIONAL HEALTHCARE CONFERENCE

FEBRUARY 13 - 14, 2020
LONDON, UNITED KINGDOM

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VII. INTERNATIONAL HEALTHCARE CONFERENCE

APRIL 15 - 16, 2020
BARCELONA, SPAIN

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VIII. INTERNATIONAL HEALTHCARE CONFERENCE

MAY 11 - 12, 2020
ISTANBUL, TURKEY

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IX. INTERNATIONAL HEALTHCARE CONFERENCE

JUNE 05 - 06, 2020
SAN FRANCISCO, UNITED STATES

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X. INTERNATIONAL HEALTHCARE CONFERENCE

JULY 20 - 21, 2020
PARIS, FRANCE

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XI. INTERNATIONAL HEALTHCARE CONFERENCE

AUGUST 10 - 11, 2020
NEW YORK, UNITED STATES

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XII. INTERNATIONAL HEALTHCARE CONFERENCE

SEPTEMBER 10 - 11, 2020
TOKYO, JAPAN

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XIII. INTERNATIONAL HEALTHCARE CONFERENCE

SEPTEMBER 16 - 17, 2020
ZÜRICH, SWITZERLAND

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XIV. INTERNATIONAL HEALTHCARE CONFERENCE

OCTOBER 21 - 22, 2020
BARCELONA, SPAIN

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XV. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 02 - 03, 2020
SAN FRANCISCO, UNITED STATES

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XVI. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 12 - 13, 2020
ISTANBUL, TURKEY

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XVII. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 19 - 20, 2020
SINGAPORE, SINGAPORE

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XVIII. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 15 - 16, 2020
BANGKOK, THAILAND

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XIX. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 28 - 29, 2020
PARIS, FRANCE

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XX. INTERNATIONAL HEALTHCARE CONFERENCE

FEBRUARY 13 - 14, 2021
LONDON, UNITED KINGDOM

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XXI. INTERNATIONAL HEALTHCARE CONFERENCE

APRIL 15 - 16, 2021
BARCELONA, SPAIN

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XXII. INTERNATIONAL HEALTHCARE CONFERENCE

MAY 11 - 12, 2021
ISTANBUL, TURKEY

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XXIII. INTERNATIONAL HEALTHCARE CONFERENCE

JUNE 05 - 06, 2021
SAN FRANCISCO, UNITED STATES

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XXIV. INTERNATIONAL HEALTHCARE CONFERENCE

JULY 20 - 21, 2021
PARIS, FRANCE

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XXV. INTERNATIONAL HEALTHCARE CONFERENCE

AUGUST 10 - 11, 2021
NEW YORK, UNITED STATES

FINISHED

XXVI. INTERNATIONAL HEALTHCARE CONFERENCE

SEPTEMBER 10 - 11, 2021
TOKYO, JAPAN

FINISHED

XXVII. INTERNATIONAL HEALTHCARE CONFERENCE

SEPTEMBER 16 - 17, 2021
ZÜRICH, SWITZERLAND

FINISHED

XXVIII. INTERNATIONAL HEALTHCARE CONFERENCE

OCTOBER 21 - 22, 2021
BARCELONA, SPAIN

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XXIX. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 02 - 03, 2021
SAN FRANCISCO, UNITED STATES

FINISHED

XXX. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 12 - 13, 2021
ISTANBUL, TURKEY

FINISHED

XXXI. INTERNATIONAL HEALTHCARE CONFERENCE

NOVEMBER 19 - 20, 2021
SINGAPORE, SINGAPORE

FINISHED

XXXII. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 15 - 16, 2021
BANGKOK, THAILAND

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XXXIII. INTERNATIONAL HEALTHCARE CONFERENCE

DECEMBER 28 - 29, 2021
PARIS, FRANCE

Healthcare Conference Call For Papers are listed below:

Previously Published Papers on "Influenza Conference"

  • Feature Extraction Technique for Prediction the Antigenic Variants of the Influenza Virus
    Authors: Majid Forghani, Michael Khachay, Keywords: Antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition. DOI:10.5281/zenodo.2021681 Abstract: In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.
  • Obese and Overweight Women and Public Health Issues in Hillah City, Iraq
    Authors: Amean A. Yasir, Zainab Kh. A. Al-Mahdi Al-Amean, Keywords: Obesity, overweight, Iraq, body mass index. DOI:10.5281/zenodo.1127400 Abstract: In both developed and developing countries, obesity among women is increasing, but in different patterns and at very different speeds. It may have a negative effect on health, leading to reduced life expectancy and/or increased health problems. This research studied the age distribution among obese women, the types of overweight and obesity, and the extent of the problem of overweight/obesity and the obesity etiological factors among women in Hillah city in central Iraq. A total of 322 overweight and obese women were included in the study, those women were randomly selected. The Body Mass Index was used as indicator for overweight/ obesity. The incidence of overweight/obesity among age groups were estimated, the etiology factors included genetic, environmental, genetic/environmental and endocrine disease. The overweight and obese women were screened for incidence of infection and/or diseases. The study found that the prevalence of 322 overweight and obese women in Hillah city in central Iraq was 19.25% and 80.78%, respectively. The obese women types were recorded based on BMI and WHO classification as class-1 obesity (29.81%), class-2 obesity (24.22%) and class-3 obesity (26.70%), the result was discrepancy non-significant, P value < 0.05. The incidence of overweight in women was high among those aged 20-29 years (90.32%), 6.45% aged 30-39 years old and 3.22% among ≥ 60 years old, while the incidence of obesity was 20.38% for those in the age group 20-29 years, 17.30% were 30-39 years, 23.84% were 40-49 years, 16.92% were 50-59 years group and 21.53% were ≥ 60 years age group. These results confirm that the age can be considered as a significant factor for obesity types (P value < 0.0001). The result also showed that the both genetic factors and environmental factors were responsible for incidents of overweight or obesity (84.78%) p value < 0.0001. The results also recorded cases of different repeated infections (skin infection, recurrent UTI and influenza), cancer, gallstones, high blood pressure, type 2 diabetes, and infertility. Weight stigma and bias generally refers to negative attitudes; Obesity can affect quality of life, and the results of this study recorded depression among overweight or obese women. This can lead to sexual problems, shame and guilt, social isolation and reduced work performance. Overweight and Obesity are real problems among women of all age groups and is associated with the risk of diseases and infection and negatively affects quality of life. This result warrants further studies into the prevalence of obesity among women in Hillah City in central Iraq and the immune response of obese women.
  • Efficacy and Stability of Ceramic Powder to Inactivate Avian Influenza Virus
    Authors: Chanathip Thammakarn, Misato Tsujimura, Keisuke Satoh, Tomomi Hasegawa, Miho Tamura, Akinobu Kawamura, Yuki Ishida, Atsushi Suguro, Hakimullah Hakim, Sakchai Ruenphet, , Kazuaki Takehara, Keywords: Avian Influenza, Ceramics, Efficacy, Stability. DOI:10.5281/zenodo.1335650 Abstract: This experiment aims to demonstrate the efficacy of ceramic powder derived from various sources to inactivate avian influenza virus and its possibility to use in the environment. The ceramics used in the present experiment were derived from chicken feces (CF), scallop shell (SS), polyvinyl chloride (PVC) and soybean (SB). All ceramics were mixed with low pathogenic AIV (LPAIV) H7N1, and then kept at room temperature. The recovered virus was titrated onto Madin-Darby canine kidney (MDCK) cells. All ceramics were assessed the inactivation stability in the environment by keeping under sunlight and under wet-dry condition until reached 7 week or 7 resuspension times respectively. The results indicate that all ceramics have excellent efficacy to inactivate LPAIV. This efficacy can be maintained under the simulated condition. The ceramics are expected to be the good materials for application in the biosecurity system at farms.
  • Computer Aided Drug Design and Studies of Antiviral Drug against H3N2 Influenza Virus
    Authors: Aditi Shukla, Ambarish S. Vidyarthi, Subir Samanta, Keywords: H3N2 Influenza, Neuraminidase, Oseltamiviranalogs, structure based drug designing DOI:10.5281/zenodo.1334902 Abstract: The worldwide prevalence of H3N2 influenza virus and its increasing resistance to the existing drugs necessitates for the development of an improved/better targeting anti-influenza drug. H3N2 influenza neuraminidase is one of the two membrane-bound proteins belonging to group-2 neuraminidases. It acts as key player involved in viral pathogenicity and hence, is an important target of anti-influenza drugs. Oseltamivir is one of the potent drugs targeting this neuraminidase. In the present work, we have taken subtype N2 neuraminidase as the receptor and probable analogs of oseltamivir as drug molecules to study the protein-drug interaction in anticipation of finding efficient modified candidate compound. Oseltamivir analogs were made by modifying the functional groups using Marvin Sketch software and were docked using Schrodinger-s Glide. Oseltamivir analog 10 was detected to have significant energy value (16% less compared to Oseltamivir) and could be the probable lead molecule. It infers that some of the modified compounds can interact in a novel manner with increased hydrogen bonding at the active site of neuraminidase and it might be better than the original drug. Further work can be carried out such as enzymatic inhibition studies; synthesis and crystallizing the drug-target complex to analyze the interactions biologically.
  • Immune Responce in Mice Immunized with Live Cold-Adapted Influenza Vaccine in Combination with Chitosan-Based Adjuvants
    Authors: Nelly К. Akhmatova, Оlga V. Lebedinskaya, Ancha V. Baranova, Еlena А. Lebedinskaya, Ekaterina V. Sorokina, Elvin А. Akhmatov, Аnatoliy P. Godovalov, Stanislav G. Markushin, Keywords: Immunophenotype, chitosan, cold-adapted vaccine, intranasal injection. DOI:10.5281/zenodo.1076860 Abstract: An influence of intranasal combined injection of live cold-adapted influenza vaccine with chitosan derivatives as adjuvants on the subpopulation structure of mononuclear leukocytes of mouse spleen which reflects the orientation of the immune response was studied. It is found that the inclusion of chitosan preparations promotes activation of cellular-level of immune response.
  • Climatic Factors Affecting on Influenza Casesin Nakhon Si Thammarat
    Authors: S. Chumkiew, W. Srisang, M. Jaroensutasinee, K. Jaroensutasinee, Keywords: Influenza, Climatic Factor, Relative Humidity,Rainy day, Wind Speed. DOI:10.5281/zenodo.1070139 Abstract: This study investigated the climatic factors associated with Influenza incidence in Nakhon Si Thammarat, Southern Thailand. Climatic factors comprised of the amount of rainfall, percent of rainy days, relative humidity, wind speed, maximum, minimum temperatures and temperature difference. A multiple stepwise regression technique was used to fit the statistical model. The result showed that the temperature difference and percent of rainy days were positively associated with Influenza incidence in Nakhon Si Thammarat.
  • In silico Analysis of Human microRNAs Targeting Influenza a Viruses (subtype H1N1, H5N1 and H3N2)
    Authors: Kritsada Khongnomnan, Wittaya Poomipak, Yong Poovorawan, Sunchai Payungporn, Keywords: Human miRNAs, Influenza A viruses, H1N1, H5N1, H3N2 DOI:10.5281/zenodo.1332618 Abstract: In this study, three subtypes of influenza A viruses (pH1N1, H5N1 and H3N2) which naturally infected human were analyzed by bioinformatic approaches to find candidate human cellular miRNAs targeting viral genomes. There were 76 miRNAs targeting influenza A viruses. Among these candidates, 70 miRNAs were subtypes specifically targeting each subtype of influenza A virus including 21 miRNAs targeted subtype H1N1, 27 miRNAs targeted subtype H5N1 and 22 miRNAs targeted subtype H3N2. The remaining 6 miRNAs target on multiple subtypes of influenza A viruses. Uniquely, hsa-miR-3145 is the only one candidate miRNA targeting PB1 gene of all three subtypes. Obviously, most of the candidate miRNAs are targeting on polymerase complex genes (PB2, PB1 and PA) of influenza A viruses. This study predicted potential human miRNAs targeting on different subtypes of influenza A viruses which might be useful for inhibition of viral replication and for better understanding of the interaction between virus and host cell.
  • Analysis of Influenza Cases and Seasonal Index in Thailand
    Authors: S. Youthao, M. Jaroensutasinee, K. Jaroensutasinee, Keywords: Influenza, disease index, seasonal index, Thailand. DOI:10.5281/zenodo.1330345 Abstract: This study investigated the pattern and seasonal index of influenza cases in Thailand. Our results showed that southern Thailand had the highest influenza incidence among the four regions of Thailand (i.e. north, northeast, central and southern Thailand). The influenza pattern in southern Thailand was similar to that of northeastern Thailand. Seasonal index values of influenza cases in Thailand were higher in the hot season than in the wet season. Influenza cases started to increase at the beginning of the hot season (April), reached a maximum in August, rapidly declined in the middle of the wet season and reached the lowest value in December. Seasonal index values for northern Thailand differed from other regions of Thailand.
  • Sequence Relationships Similarity of Swine Influenza a (H1N1) Virus
    Authors: Patsaraporn Somboonsak, Mud-Armeen Munlin, Keywords: Sequence DNA, Relationship of swine, Swineinfluenza, Sequence Similarity DOI:10.5281/zenodo.1056454 Abstract: In April 2009, a new variant of Influenza A virus subtype H1N1 emerged in Mexico and spread all over the world. The influenza has three subtypes in human (H1N1, H1N2 and H3N2) Types B and C influenza tend to be associated with local or regional epidemics. Preliminary genetic characterization of the influenza viruses has identified them as swine influenza A (H1N1) viruses. Nucleotide sequence analysis of the Haemagglutinin (HA) and Neuraminidase (NA) are similar to each other and the majority of their genes of swine influenza viruses, two genes coding for the neuraminidase (NA) and matrix (M) proteins are similar to corresponding genes of swine influenza. Sequence similarity between the 2009 A (H1N1) virus and its nearest relatives indicates that its gene segments have been circulating undetected for an extended period. Nucleic acid sequence Maximum Likelihood (MCL) and DNA Empirical base frequencies, Phylogenetic relationship amongst the HA genes of H1N1 virus isolated in Genbank having high nucleotide sequence homology. In this paper we used 16 HA nucleotide sequences from NCBI for computing sequence relationships similarity of swine influenza A virus using the following method MCL the result is 28%, 36.64% for Optimal tree with the sum of branch length, 35.62% for Interior branch phylogeny Neighber – Join Tree, 1.85% for the overall transition/transversion, and 8.28% for Overall mean distance.
  • Climatic Factors Affecting Influenza Cases in Southern Thailand
    Authors: S. Youthao, M. Jaroensutasinee, K. Jaroensutasinee, Keywords: Influenza, Climatic Factor, Relative Humidity, Rainfall, Pressure, Wind Speed, sunshine duration, Temperature, Andaman Sea, Gulf of Thailand, Southern Thailand. DOI:10.5281/zenodo.1329821 Abstract: This study investigated climatic factors associated with influenza cases in Southern Thailand. The main aim for use regression analysis to investigate possible causual relationship of climatic factors and variability between the border of the Andaman Sea and the Gulf of Thailand. Southern Thailand had the highest Influenza incidences among four regions (i.e. north, northeast, central and southern Thailand). In this study, there were 14 climatic factors: mean relative humidity, maximum relative humidity, minimum relative humidity, rainfall, rainy days, daily maximum rainfall, pressure, maximum wind speed, mean wind speed, sunshine duration, mean temperature, maximum temperature, minimum temperature, and temperature difference (i.e. maximum – minimum temperature). Multiple stepwise regression technique was used to fit the statistical model. The results indicated that the mean wind speed and the minimum relative humidity were positively associated with the number of influenza cases on the Andaman Sea side. The maximum wind speed was positively associated with the number of influenza cases on the Gulf of Thailand side.

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