Spatio-temporal modeling of co-dynamics of smallpox, measles, and pertussis in pre-healthcare Finland.
Bayesian analysis
Infection co-dynamics
Measles
Pertussis
Smallpox
Spatio-temporal
Journal
PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425
Informations de publication
Date de publication:
2024
2024
Historique:
received:
06
02
2024
accepted:
01
09
2024
medline:
30
9
2024
pubmed:
30
9
2024
entrez:
30
9
2024
Statut:
epublish
Résumé
Infections are known to interact as previous infections may have an effect on risk of succumbing to a new infection. The co-dynamics can be mediated by immunosuppression or modulation, shared environmental or climatic drivers, or competition for susceptible hosts. Research and statistical methods in epidemiology often concentrate on large pooled datasets, or high quality data from cities, leaving rural areas underrepresented in literature. Data considering rural populations are typically sparse and scarce, especially in the case of historical data sources, which may introduce considerable methodological challenges. In order to overcome many obstacles due to such data, we present a general Bayesian spatio-temporal model for disease co-dynamics. Applying the proposed model on historical (1820-1850) Finnish parish register data, we study the spread of infectious diseases in pre-healthcare Finland. We observe that measles, pertussis, and smallpox exhibit positively correlated dynamics, which could be attributed to immunosuppressive effects or, for example, the general weakening of the population due to recurring infections or poor nutritional conditions.
Identifiants
pubmed: 39346083
doi: 10.7717/peerj.18155
pii: 18155
pmc: PMC11439382
doi:
Types de publication
Journal Article
Historical Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e18155Informations de copyright
©2024 Pasanen et al.
Déclaration de conflit d'intérêts
The authors declare there are no competing interests.