Extended-spectrum β-lactamase- and AmpC β-lactamase-producing Enterobacterales associated with urinary tract infections in the New Zealand community: a case-control study.

Objectives: To assess whether having a pet in the home is a risk factor for community-acquired urinary tract infections associated with extended-spectrum β-lactamase (ESBL)- or AmpC β-lactamase (ACBL)- producing Enterobacterales.

Methods: An unmatched case-control study was conducted between August 2015 and September 2017. Cases (n = 141) were people with community-acquired urinary tract infection (UTI) caused by ESBL- or ACBL-producing Enterobacterales.

Carriage of Extended-Spectrum-Beta-Lactamase- and AmpC Beta-Lactamase-Producing Escherichia coli Strains from Humans and Pets in the Same Households.

Extended-spectrum-beta-lactamase (ESBL)- or AmpC beta-lactamase (ACBL)-producing bacteria are the most common cause of community-acquired multidrug-resistant urinary tract infections (UTIs) in New Zealand. The carriage of antimicrobial-resistant bacteria has been found in both people and pets from the same household; thus, the home environment may be a place where antimicrobial-resistant bacteria are shared between humans and pets. In this study, we sought to determine whether members (pets and people) of the households of human index cases with a UTI caused by an ESBL- or ACBL-producing strain also carried an ESBL- or ACBL-producing strain and, if so, whether it was a clonal match to the index case clinical strain.

Generalised probability mass function for the final epidemic size of an SIR model on a line of triangles network.

We explore the feasibility of deriving generalised expressions for the probability mass function (PMF) of the final epidemic size of a Susceptible - Infected - Recovered (SIR) model on a finite network of an arbitrary number of nodes. Expressions for the probability that the infection progresses along a given pathway in a line of triangles (LoT) network are presented. Deriving expressions for the probability that the infection ends at any given node allows us to determine the corresponding final size of the epidemic, and hence produce PMFs of the final epidemic size.

Eight challenges in modelling disease ecology in multi-host, multi-agent systems.

Many disease systems exhibit complexities not captured by current theoretical and empirical work. In particular, systems with multiple host species and multiple infectious agents (i.e.

Modeling infectious disease dynamics in the complex landscape of global health.

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs.

Modelling the evolution and spread of HIV immune escape mutants.

During infection with human immunodeficiency virus (HIV), immune pressure from cytotoxic T-lymphocytes (CTLs) selects for viral mutants that confer escape from CTL recognition. These escape variants can be transmitted between individuals where, depending upon their cost to viral fitness and the CTL responses made by the recipient, they may revert. The rates of within-host evolution and their concordant impact upon the rate of spread of escape mutants at the population level are uncertain.

Key transmission parameters of an institutional outbreak during the 1918 influenza pandemic estimated by mathematical modelling.

Aim: To estimate the key transmission parameters associated with an outbreak of pandemic influenza in an institutional setting (New Zealand 1918).

Methods: Historical morbidity and mortality data were obtained from the report of the medical officer for a large military camp. A susceptible-exposed-infectious-recovered epidemiological model was solved numerically to find a range of best-fit estimates for key epidemic parameters and an incidence curve.