HPAI Outbreak Temporal Analysis

Phase 1: December 20, 2025 - January 13, 2026

Published

February 16, 2026

Introduction

This report presents a temporal analysis of the ongoing HPAI (Highly Pathogenic Avian Influenza) outbreak affecting poultry farms in the region. The analysis covers the period from December 20, 2025 through January 13, 2026, examining epidemic curves, detection patterns, and response timelines.

Setup and Data Loading

Data Summary

This analysis includes 103 confirmed HPAI cases spanning from December 22, 2025 to January 13, 2026 (a period of 22 days).

Data completeness: 4 case(s) are missing the date of suspicion, which affects detection delay calculations for those cases. These cases were detected through methods that may not have a clear “suspicion” date (likely preshipment testing or contact tracing).

Epidemic Curves

Primary Epidemic Curve

Figure 1: Daily epidemic curve showing HPAI cases by date of suspicion and date of confirmation. The 7-day moving average (red line) smooths daily variation to show the underlying trend.

The epidemic curve shows exponential growth in the early phase of the outbreak (late December 2025), with cases detected through both passive surveillance (following clinical suspicion) and confirmation. The peak detection period occurred around January 12 with 17 cases confirmed in a single day.

The 7-day moving average indicates sustained transmission throughout the observation period, with the outbreak showing signs of continued acceleration by mid-January 2026.

Weekly Epidemic Curve

Figure 2: Weekly epidemic curve showing HPAI cases by detection method. Stacked bars show the composition of detection methods, while the line shows cumulative case count. Week labels indicate the Monday start date of each epidemiological week.
Table 1: Weekly case summary showing progression of the outbreak and detection method composition
Week Start Date Weekly Cases Cumulative Growth Rate (%)
Week 1 Dec 22 4 4 NA
Week 2 Dec 29 20 24 400.0
Week 3 Jan 05 48 72 140.0
Week 4 Jan 12 31 103 -35.4

The weekly analysis reveals:

  • Week 1-2 (Dec 20-Jan 2): Initial exponential growth phase with 24 cases
  • Week 3 (Jan 3-9): Peak detection period with sustained high case counts
  • Week 4 (Jan 10-13): Continued detection at elevated levels (incomplete week)

Growth Rate Analysis

Table 2: Outbreak growth metrics calculated from the early exponential phase (first 14 days)
Metric Value Interpretation
Daily growth rate (r) 0.228 22.8% daily increase
Doubling time (days) 3.0 Days to double case count
Estimated R₀ 3.93 Avg. secondary cases per case
Generation time assumed (days) 6 Typical HPAI transmission
Figure 3: Log-scale plot of cumulative cases during the early outbreak period showing exponential growth pattern. The fitted line represents the exponential growth model used to calculate doubling time.

The early outbreak phase demonstrates moderate exponential growth with a doubling time of approximately 3.0 days. This growth rate is consistent with sustained transmission and suggests that control measures were needed to interrupt transmission chains.

Detection Delays

Time from Suspicion to Confirmation

Among the 99 cases with complete date information, the time from suspicion to laboratory confirmation averaged 1.9 days (median: 2.0 days, IQR: 1.0-2.0 days).

Table 3: Summary statistics for detection delay (days from suspicion to confirmation)
Statistic Days
N Cases 99.0
Mean 1.9
Median 2.0
SD 1.0
Min 1.0
Q1 1.0
Q3 2.0
Max 5.0
Figure 4: Distribution of detection delays showing time from clinical suspicion to laboratory confirmation. The red dashed line indicates the median delay.

Detection delays are generally short, reflecting efficient laboratory testing and reporting systems. The distribution shows:

  • Minimum delay: 1 day(s) - indicating same-day or next-day confirmation possible
  • Maximum delay: 5 days - may represent cases with initial negative results or testing delays
  • Most cases (50%) confirmed within 1.0-2.0 days of suspicion

Detection Delay Over Time

Figure 5: Temporal trend in detection delays throughout the outbreak period. The smoothed line (loess) shows whether detection efficiency improved or declined over time. Points are colored by detection method.

The temporal trend analysis reveals whether detection efficiency changed as the outbreak progressed. The smoothed trend line indicates that detection delays remained consistently short, suggesting laboratory capacity kept pace with case load.

Detection Delay by Method

Table 4: Detection delays stratified by surveillance method. Sample sizes and summary statistics are shown for each detection pathway.
Detection Method N Mean (days) Median (days) SD Range
Passive 96 1.9 2 1 1-5
Preshipment 3 1.0 1 0 1-1
Note:
Kruskal-Wallis test: χ² = 3.50, p = 0.061

Comparison across detection methods shows:

  • Passive surveillance (96 cases): Mean delay 1.9 days - reflects clinical detection and farmer reporting
  • Preshipment testing (3 cases): Mean delay 1.0 days - may detect subclinical infections
  • Contact tracing (0 cases): No cases with delay data or suspicion dates - proactive surveillance

Detection delays appear similar across methods, indicating consistent laboratory processing regardless of detection pathway.

Summary

This temporal analysis of the HPAI outbreak reveals:

  1. Epidemic Pattern: 103 cases detected over 22 days showing rapid exponential growth

  2. Detection Efficiency: Median confirmation delay of 2.0 days demonstrates efficient laboratory systems

  3. Surveillance Performance: Detection primarily through passive surveillance, with consistent delays across methods

Next steps: Spatial analysis to identify outbreak clusters and risk factor analysis to determine farm characteristics associated with infection risk.