Epidemiological delays are key quantities that inform public health policy and clinical practice. They are used as inputs for mathematical and statistical models, which in turn can guide control strategies. In recent work, we found that censoring, right truncation, and dynamical bias were rarely addressed correctly when estimating delays and that these biases were large enough to have knock-on impacts across a large number of use cases. Here, we formulate a checklist of best practices for estimating and reporting epidemiological delays. We also provide a flowchart to guide practitioners based on their data. Our examples are focused on the incubation period and serial interval due to their importance in outbreak response and modeling, but our recommendations are applicable to other delays. The recommendations, which are based on the literature and our experience estimating epidemiological delay distributions during outbreak responses, can help improve the robustness and utility of reported estimates and provide guidance for the evaluation of estimates for downstream use in transmission models or other analyses.

Bats, rodents and monkeys are reservoirs for emerging zoonotic infections. We sought to describe the frequency of human exposure to these animals and the seasonal and geographic variation of these exposures in Bangladesh. During 2013-2016, we conducted a cross-sectional survey in a nationally representative sample of 10,002 households from 1001 randomly selected communities. We interviewed household members about exposures to bats, rodents and monkeys, including a key human-bat interface-raw date palm sap consumption. Respondents reported observing rodents (90%), bats (52%) and monkeys (2%) in or around their households, although fewer reported direct contact. The presence of monkeys around the household was reported more often in Sylhet division (7%) compared to other divisions. Households in Khulna (17%) and Rajshahi (13%) were more likely to report drinking date palm sap than in other divisions (1.5-5.6%). Date palm sap was mostly consumed during winter with higher frequencies in January (16%) and February (12%) than in other months (0-5.6%). There was a decreasing trend in drinking sap over the three years. Overall, we observed substantial geographic and seasonal patterns in human exposure to animals that could be sources of zoonotic disease. These findings could facilitate targeting emerging zoonoses surveillance, research and prevention efforts to areas and seasons with the highest levels of exposure.

Contact patterns play a key role in disease transmission, and variation in contacts during the course of illness can influence transmission, particularly when accompanied by changes in host infectiousness. We used surveys among 1,642 contacts of 94 Nipah case-patients in Bangladesh to determine how contact patterns (physical and with bodily fluids) changed as disease progressed in severity. The number of contacts increased with severity and, for case-patients who died, peaked on the day of death. Given transmission has only been observed among fatal Nipah cases, our findings suggest changes in contact patterns during illness contribute to risk of infection.

BACKGROUND: Nipah virus is a highly virulent zoonotic pathogen that can be transmitted between humans. Understanding the dynamics of person-to-person transmission is key to designing effective interventions. METHODS: We used data from all Nipah virus cases identified during outbreak investigations in Bangladesh from April 2001 through April 2014 to investigate case-patient characteristics associated with onward transmission and factors associated with the risk of infection among patient contacts. RESULTS: Of 248 Nipah virus cases identified, 82 were caused by person-to-person transmission, corresponding to a reproduction number (i.e., the average number of secondary cases per case patient) of 0.33 (95% confidence interval [CI], 0.19 to 0.59). The predicted reproduction number increased with the case patient's age and was highest among patients 45 years of age or older who had difficulty breathing (1.1; 95% CI, 0.4 to 3.2). Case patients who did not have difficulty breathing infected 0.05 times as many contacts (95% CI, 0.01 to 0.3) as other case patients did. Serologic testing of 1863 asymptomatic contacts revealed no infections. Spouses of case patients were more often infected (8 of 56 [14%]) than other close family members (7 of 547 [1.3%]) or other contacts (18 of 1996 [0.9%]). The risk of infection increased with increased duration of exposure of the contacts (adjusted odds ratio for exposure of >48 hours vs. </=1 hour, 13; 95% CI, 2.6 to 62) and with exposure to body fluids (adjusted odds ratio, 4.3; 95% CI, 1.6 to 11). CONCLUSIONS: Increasing age and respiratory symptoms were indicators of infectivity of Nipah virus. Interventions to control person-to-person transmission should aim to reduce exposure to body fluids. (Funded by the National Institutes of Health and others.).

Piszczek and Parlow1 outlined expected benefits of a stepped-wedge cluster trial (SWCT) design, with specific reference to the Sierra Leone Trial to Introduce a Vaccine against Ebola (STRIVE). STRIVE, however, is not an SWCT, but a phased-rollout trial in which randomization to immediate or delayed vaccination arms occurs at the individual level (RCT) within trial clusters.2 While the SWCT design is advantageous in certain circumstances, many of the benefits described by Piszczek and Parlow would not apply to evaluation of Ebola vaccine candidates in Sierra Leone. | In a recently published study, we used simulations to compare statistical validity and power for an SWCT and a STRIVE-like RCT in the same trial population.3 Piszczek and Parlow contend that an SWCT can achieve greater statistical power than an RCT via multiple before-and-after and between-group comparisons; however, we found that the declining and heterogeneous epidemic incidence across Sierra Leone undermine such cluster-level comparisons and, consequently, the power of an SWCT. Specifically, we estimated that the SWCT design would be 3–10 times less likely than an individually randomized, phased roll-out RCT to definitively identify an efficacious vaccine. For example, an SWCT starting in April 2015 was expected to have a less than 10% chance of detecting the effect of a 90% efficacious vaccine.