Literary award · United Kingdom · since 2006

CWA International Dagger

Award given by the Crime Writers' Association. Established 2006 in United Kingdom.

About CWA International Dagger

The CWA International Dagger (formerly known as the Duncan Lawrie International Dagger and the Crime Fiction in Translation Dagger) is an award given by the Crime Writers' Association for best translated crime novel of the year. The winning author and translator receives an ornamental Dagger at an award ceremony held annually. Until 2005, translated crime novels were eligible to be nominated for the CWA Gold Dagger. From 2006, translated crime fiction was honored with its own award conceived partly to recognize the contribution of the translator in international works. Until 2008 the International Dagger was named for its sponsor, the Duncan Lawrie Private Bank. In three of the first four years it was awarded, it was won by Fred Vargas and her translator Siân Reynolds.

From the Wikipedia article “CWA International Dagger”, licensed under CC BY-SA 4.0.

Recent winners

YearWinnerWinning work
2019Daniella Zamir—
2018Henning MankellAfter the Fire
2017Leif G. W. PerssonThe Dying Detective
2016Pierre LemaitreThe Great Swindle
2015Pierre LemaitreCamille
2014Arturo Pérez-ReverteThe Siege
2013Pierre LemaitreAlex
2013Fred VargasL'Armée furieuse
2012Andrea CamilleriThe Potter's Field
2011Roslund & HellströmThree Seconds
2010Johan Theorin—
2009Fred VargasThe Chalk Circle Man
2007Fred VargasSous les vents de Neptune

From Wikidata; the list may be incomplete for some years.

Eligibility and entering

Check the official rules of the CWA International Dagger for the current eligibility window, accepted formats, residency or language requirements and any entry fee. For most established prizes the publisher submits on the author's behalf, often with a limit on entries per imprint.

If you are self-published, look for an explicit statement that independently published books are accepted, and budget for entry fees and copies for judges.

Sources & data