Haryana H1N1 2009-2011 - 14 fatalities this season - Total 52

[Ronan Kelly]

Re: Haryana H1N1 - 11 fatalities this season - Total 49

Re: Haryana H1N1 - 11 fatalities this season - Total 49

?Weather change makes swine flu virus active?
Raakhi Jagga

Posted: Sat Mar 12 2011, 02:24 hrs
Ludhiana:



...

Two patients have already died of swine flu this week; they were from Moga and Haryana. Giving data, Dr Bhatia said, ?In the post-pandemic period from August onwards, a total of 37 cases have been reported from Punjab, of which 17 resulted in death. Out of these 37 cases, nearly 15 patients are from February onwards. Although no clear reason is there, it seems that the change of season is the reason for the virus becoming active. The same happened when winter was approaching.?

...
http://www.indianexpress.com/news/weather-change-makes-swine-flu-virus-active/761386/

 

[Ronan Kelly]

Re: Haryana H1N1 - 12 fatalities this season - Total 50

Re: Haryana H1N1 - 12 fatalities this season - Total 50

Latest PIB release puts total fatalities at 52.

http://pib.nic.in/newsite/erelease.aspx?relid=71210

 

[Ronan Kelly]

Comment: It would seem that H1N1 was not the prevalent influenza virus in Haryana in 2011. The paper below (h/t tetano) shows detections only for B and H3N2. - Ro



PLoS One. 2018 Apr 26;13(4):e0196495. doi: 10.1371/journal.pone.0196495. eCollection 2018.
Estimation of community-level influenza-associated illness in a low resource rural setting in India.

Saha S[SUP]1[/SUP], Gupta V[SUP]2[/SUP], Dawood FS[SUP]3[/SUP], Broor S[SUP]4[/SUP], Lafond KE[SUP]3[/SUP], Chadha MS[SUP]5[/SUP], Rai SK[SUP]2[/SUP], Krishnan A[SUP]2[/SUP].
Author information

Abstract

OBJECTIVE:

To estimate rates of community-level influenza-like-illness (ILI) and influenza-associated ILI in rural north India.
METHODS:

During 2011, we conducted household-based healthcare utilization surveys (HUS) for any acute medical illness (AMI) in preceding 14days among residents of 28villages of Ballabgarh, in north India. Concurrently, we conducted clinic-based surveillance (CBS) in the area for AMI episodes with illness onset ≤3days and collected nasal and throat swabs for influenza virus testing using real-time polymerase chain reaction. Retrospectively, we applied ILI case definition (measured/reported fever and cough) to HUS and CBS data. We attributed 14days of risk-time per person surveyed in HUS and estimated community ILI rate by dividing the number of ILI cases in HUS by total risk-time. We used CBS data on influenza positivity and applied it to HUS-based community ILI rates by age, month, and clinic type, to estimate the community influenza-associated ILI rates.
FINDINGS:

The HUS of 69,369 residents during the year generated risk-time of 3945 person-years (p-y) and identified 150 (5%, 95%CI: 4-6) ILI episodes (38 ILI episodes/1,000 p-y; 95% CI 32-44). Among 1,372 ILI cases enrolled from clinics, 126 (9%; 95% CI 8-11) had laboratory-confirmed influenza (A (H3N2) = 72; B = 54). After adjusting for age, month, and clinic type, overall influenza-associated ILI rate was 4.8/1,000 p-y; rates were highest among children <5 years (13; 95% CI: 4-29) and persons≥60 years (11; 95%CI: 2-30).
CONCLUSION:

We present a novel way to use HUS and CBS data to generate estimates of community burden of influenza. Although the confidence intervals overlapped considerably, higher point estimates for burden among young children and older adults shows the utility for exploring the value of influenza vaccination among target groups.


PMID: 29698505 DOI: 10.1371/journal.pone.0196495