APA (7th ed.) Citation

MV, E., FA, I., M, R., AT, A., MH, B., KE, F., . . . A, G. (2023). Applying a zero-corrected, gravity model estimator reduces bias due to heterogeneity in healthcare utilization in community-scale, passive surveillance datasets of endemic diseases. Scientific reports, 13(1), 21288. https://doi.org/10.1038/s41598-023-48390-0

Chicago Style (17th ed.) Citation

MV, Evans, et al. "Applying a Zero-corrected, Gravity Model Estimator Reduces Bias Due to Heterogeneity in Healthcare Utilization in Community-scale, Passive Surveillance Datasets of Endemic Diseases." Scientific Reports 13, no. 1 (2023): 21288. https://doi.org/10.1038/s41598-023-48390-0.

MLA (9th ed.) Citation

MV, Evans, et al. "Applying a Zero-corrected, Gravity Model Estimator Reduces Bias Due to Heterogeneity in Healthcare Utilization in Community-scale, Passive Surveillance Datasets of Endemic Diseases." Scientific Reports, vol. 13, no. 1, 2023, p. 21288, https://doi.org/10.1038/s41598-023-48390-0.