  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.
