Florence Under Siege: Surviving Plague in an Early Modern City
John Henderson
A vivid recreation of how the governors and governed of early seventeenth-century Florence confronted, suffered, and survived a major epidemic of plague. Plague remains the paradigm against which reactions to many epidemics are often judged. Here, John Henderson examines how a major city fought, suffered, and survived the impact of plague. Going beyond traditional oppositions between rich and poor, this book provides a nuanced and more compassionate interpretation of government policies in practice, by recreating the very human reactions and survival strategies of families and individuals. From the evocation of the overcrowded conditions in isolation hospitals to the splendor of religious processions, Henderson analyzes Florentine reactions within a wider European context to assess the effect of state policies on the city, street, and family. Writing in a vivid and approachable way, this book unearths the forgotten stories of doctors and administrators struggling to cope with the sick and dying, and of those who were left bereft and confused by the sudden loss of relatives.
Award History
0 wins · 1 total
| Award | Year | Result | Category / Notes |
|---|---|---|---|
| Cundill History PrizeMajor | 2020 | Longlist | Secondary source |
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies
This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.
01 Central figures
None extracted with sufficient confidence.
02 Central places
- Florence86%
03 Suggested argument
The book argues that early seventeenth-century Florence’s plague experience was shaped by state policies in practice, producing nuanced outcomes for both government actors and ordinary families beyond simple rich-versus-poor explanations.
Model confidence 64%
04 Reading orientation
65 / 100 academicAcademic
An estimate of intended readership and scholarly apparatus—not quality or importance.
Confidence percentages are the model's own estimates. Profile confidence: 78%.