Association between precipitation events, drought, and animal operations with Salmonella infections in the Southwest US, 2009-2021

Abstract

Background: Temperature and precipitation have previously been associated with Salmonella infections. The association between salmonellosis and precipitation might be explained by antecedent drought conditions; however, few studies have explored this effect.

Methods: Using an ecological study design with public health surveillance, meteorological (total precipitation [inches], temperature [average °F], Palmer Drought Severity Index [PDSI, category]), and livestock data we explored the association between precipitation and Salmonella infections reported in 127/141 counties from 2009 to 2021 in the Southwest, US and determined how this association was modified by antecedent drought. To explore the acute effect of precipitation on Salmonella infections we used negative binomial generalized estimating equations adjusted for temperature with a 2-week lag resulting in Incidence Rate Ratios (IRR). Stratified analyses were used to explore the effect of antecedent drought and type of animal density on this association.

Results: A one inch increase in precipitation was associated with a 2 % increase in Salmonella infections reported two weeks later (IRR: 1.02, 95 % CI: 1.00, 1.04) after adjusting for average temperature and PDSI. Precipitation following moderate (IRR: 1.22, 95 % CI: 1.17, 1.28) and severe drought (IRR: 1.16, 95 % CI: 1.10, 1.22) was associated with a significant increase in cases, whereas in the most extreme drought conditions, cases were significantly decreased (IRR: 0.89, 95 % CI: 0.85, 0.94). Overall, more precipitation (above a 30-year normal, the 95th and 99th percentiles) were associated with greater increases in cases, with the highest increase following moderate and severe drought. Counties with a higher density of chicken and beef cattle were significantly associated with increased cases regardless of drought status, whereas dairy cattle, and cattle including calves had mixed results.

Discussion: Our study suggests precipitation following prior dry conditions is associated with an increase in salmonellosis in the Southwest, US. Public health is likely to see an increase in salmonellosis with extreme precipitation events, especially in counties with a high density of chicken and beef cattle.

Keywords: Climate change; Drought; Enteric diseases; Environmental epidemiology; Precipitation; Salmonella.

Fig. 1

IRR (marker) and 95 % CI (band) for the association between a one-inch increase in total weekly precipitation during different levels of drought via the PDSI (colors) in an ecological analysis of Salmonella infections in the Southwest US, 2009–2021. IRR, Incidence Rate Ratio; CI, Confidence Interval; PDSI, Palmer Drought Severity Index. IRRs and 95 % CIs for all models available in Table S6 of the Supplemental Material. Dashed line indicates null value, where the risk of the outcome in both the exposed and non-exposed groups are equal. Estimates are based on negative binomial generalized estimating equations. The crude IRR (first marker, in black) provides the estimate for a one-inch increase in total weekly precipitation on Salmonella cases adjusted for average temperature. The next estimates are for a one-inch increase in total weekly precipitation, stratified by antecedent conditions. Antecedent conditions are measured via the PDSI (each of the next 6 markers, in color from teal to red: Extremely Wet, ≥4; Very Wet, 3–3.9; Moderately Wet, 2–2.9; Normal, −1.9-1.9; Moderate Drought, −2 to −2.9; Severe Drought, −3 to −3.9; and Extreme Drought, ≤ − 4). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 2

IRR (marker) and 95 % CI (line) comparing counties which have experienced different levels of extreme precipitation events, compared to those who have not during different levels of drought via the PDSI in an ecological analysis of Salmonella infections in the Southwest US, 2009–2021. IRR, Incidence Rate Ratio; CI, Confidence Interval; PDSI, Palmer Drought Severity Index. IRRs and 95 % CIs for all models available in Table S6 of the Supplemental Material. Dashed line indicates null value, where the risk of the outcome in both the exposed and non-exposed groups are equal. Estimates are based on negative binomial generalized estimating equations. Colors indicate the level of precipitation defined as (light teal) heavy precipitation (defined as total precipitation in the week over the 30-year normal), (teal) total precipitation above the 95th percentile, and (dark teal) total precipitation above the 99th percentile. The first set of markers (crude IRR) provides the estimate for comparing counties which have experienced that level of total weekly precipitation in a given week, to counties which have not. The next estimates compare counties which experienced that level of precipitation, to those that have not, stratified by antecedent conditions. Antecedent conditions are measured via the PDSI (each of the next 6 markers, in color from teal to red: Extremely Wet, ≥4; Very Wet, 3–3.9; Moderately Wet, 2–2.9; Normal, −1.9-1.9; Moderate Drought, −2 to −2.9; Severe Drought, −3 to −3.9; and Extreme Drought, ≤ − 4). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 3

IRR (marker) and 95 % CI (band) for the association between a one-inch increase in precipitation during different levels of drought via the PDSI adjusted for counties with different animal density types per square mile in an ecological analysis of Salmonella infections in the Southwest US, 2009–2021. IRR, Incidence Rate Ratio; CI, Confidence Interval; PDSI, Palmer Drought Severity Index. IRRs and 95 % CIs for all models available in Table S6 of the Supplemental Material. Dashed line indicates null value, where the risk of the outcome in both the exposed and non-exposed groups are equal. Estimates are based on negative binomial generalized estimating equations. The crude IRR (first marker, in black) provides the estimate for a one-inch increase in total weekly precipitation on Salmonella cases adjusted for animal density and average temperature. The next estimates are stratified by antecedent conditions for a one-unit increase in density of each livestock type for a one-inch increase in total weekly precipitation on Salmonella cases in counties with these operations compared to those without. Antecedent conditions are measured via the PDSI (each of the next 6 markers, in color from teal to red: Extremely Wet, ≥4; Very Wet, 3–3.9; Moderately Wet, 2–2.9; Normal, −1.9-1.9; Moderate Drought, −2 to −2.9; Severe Drought, −3 to −3.9; and Extreme Drought, ≤ − 4). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)