ArticlePloS one2013
Climate variability, weather and enteric disease incidence in New Zealand: time series analysis.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
30 citing papers in PubMed, 78 citations in OpenAlex.
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- Seasonally varying effects of improved water, sanitation and handwashing interventions on Giardia infection in Bangladesh.medRxiv : the preprint server for health sciences · 2025Article
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- The Impact of Antibiotic Resistance in Childhood Campylobacter Infections Before and After the COVID-19 Pandemic in the Southeast Region of Romania.Antibiotics (Basel, Switzerland) · 2025Article
- Disparities in Salmonellosis Incidence for US Counties with Different Social Determinants of Health Profiles Are Also Mediated by Extreme Weather: A Counterfactual Analysis of Laboratory Enteric Disease Surveillance (LEDS) Data From 1997 through 2019.Journal of food protection · 2024Article
- Molecular characterization of Giardia duodenalis, Cryptosporidium spp., and Entamoeba spp. infecting domestic and feral/stray cats in Jordan.Parasitology research · 2024Article
- Association between periodic variation of air temperature, humidity, atmospheric pressure and hospital admissions for acute occlusive mesenteric ischaemia.Scientific reports · 2024Article
- Severe weather events and cryptosporidiosis in Aotearoa New Zealand: A case series of space-time clusters.Epidemiology and infection · 2024Article
- Environmental Factors Associated withPathogens (Basel, Switzerland) · 2023Review
- Epidemiologic and Clinical Features ofJournal of Korean medical science · 2023Article
- Dairy Cattle Density and Temporal Patterns of Human Campylobacteriosis and Cryptosporidiosis in New Zealand.EcoHealth · 2022Article
- Interrelationship between climatic factors and incidence of FBD caused by Clostridioides difficile toxin B, Clostridium perfringens, Campylobacter spp., and Escherichia coli O157:H7.Environmental science and pollution research international · 2021Article
- Edaphoclimatic seasonal trends and variations of theInfectious Disease Modelling · 2021Article
- Comparison of heat-illness associations estimated with different temperature metrics in the Australian Capital Territory, 2006-2016.International journal of biometeorology · 2020Article
- Small-scaled association between ambient temperature and campylobacteriosis incidence in Germany.Scientific reports · 2020Article
- Species and genotypes causing human cryptosporidiosis in New Zealand.Parasitology research · 2020Article
- Distinct climate influences on the risk of typhoid compared to invasive non-typhoid Salmonella disease in Blantyre, Malawi.Scientific reports · 2019Article
- Interrelationships between Multiple Climatic Factors and Incidence of Foodborne Diseases.International journal of environmental research and public health · 2018Article
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Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEvaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases.
objectivesTo examine the associations between regional climate variability and enteric disease incidence in New Zealand.
methodsAssociations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models.
resultsNo climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β = 0.130, SE = 0.060, p <0.01) and inversely related to the Southern Oscillation Index (SOI) two months previously (β = -0.008, SE = 0.004, p <0.05). By contrast, salmonellosis was positively associated with temperature (β = 0.110, SE = 0.020, p<0.001) of the current month and SOI of the current (β = 0.005, SE = 0.002, p<0.050) and previous month (β = 0.005, SE = 0.002, p<0.05). Forecasting accuracy of the multivariate models for cryptosporidiosis and salmonellosis were significantly higher.
conclusionsAlthough spatial heterogeneity in the observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.
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