Skip to main content
PLOS Neglected Tropical Diseases logoLink to PLOS Neglected Tropical Diseases
. 2022 Apr 20;16(4):e0010358. doi: 10.1371/journal.pntd.0010358

Optimizing one-dose and two-dose cholera vaccine allocation in outbreak settings: A modeling study

Tiffany Leung 1, Julia Eaton 2, Laura Matrajt 1,*
Editor: James Michael Fleckenstein3
PMCID: PMC9060364  PMID: 35442958

Abstract

Background

A global stockpile of oral cholera vaccine (OCV) was established in 2013 for use in outbreak response and are licensed as two-dose regimens. Vaccine availability, however, remains limited. Previous studies have found that a single dose of OCV may provide substantial protection against cholera.

Methods

Using a mathematical model with two age groups paired with optimization algorithms, we determine the optimal vaccination strategy with one and two doses of vaccine to minimize cumulative overall infections, symptomatic infections, and deaths. We explore counterfactual vaccination scenarios in three distinct settings: Maela, the largest refugee camp in Thailand, with high in- and out-migration; N’Djamena, Chad, a densely populated region; and Haiti, where departments are connected by rivers and roads.

Results

Over the short term under limited vaccine supply, the optimal strategies for all objectives prioritize one dose to the older age group (over five years old), irrespective of setting and level of vaccination coverage. As more vaccine becomes available, it is optimal to administer a second dose for long-term protection. With enough vaccine to cover the whole population with one dose, the optimal strategies can avert up to 30% to 90% of deaths and 36% to 92% of symptomatic infections across the three settings over one year. The one-dose optimal strategies can avert 1.2 to 1.8 times as many cases and deaths compared to the standard two-dose strategy.

Conclusions

In an outbreak setting, speedy vaccination campaigns with a single dose of OCV is likely to avert more cases and deaths than a two-dose pro-rata campaign under a limited vaccine supply.

Author summary

Cholera is a major global burden, with 21,000–143,000 deaths annually. The oral cholera vaccine (OCV) is given as two doses and is less effective in children under five years old than in those aged five years and older. However, supply is limited. In this study, we used mathematical models paired with optimization algorithms to find the optimal strategies to allocate vaccines in order to minimize the number of cases and deaths for three distinct settings in Chad, Thailand, and Haiti. We found that in the short term (1 year) when there is limited vaccine supply, it is optimal to vaccinate individuals over five years old with one dose and young children under five years old with two doses. Across the three settings, these optimal strategies prevent the most cases, save the most lives, and avert 1.2 to 1.8 times as many cases and deaths as the standard two-dose untargeted strategy. Our results support that if vaccine supply is limited, under an outbreak setting, mass vaccination campaigns with a single dose of OCV may prevent more cases and save more lives than would a standard two-dose untargeted campaign.

Introduction

Cholera is an infectious disease caused by Vibrio cholerae with an estimated 1.3 to 4 million cases and 21,000 to 143,000 deaths annually [1], particularly in sub-Saharan Africa or displaced populations. Improved access to water, sanitation, and hygiene (WASH) is the mainstay of long-term cholera control and prevention. For the short to medium term, until WASH improvements are established, vaccination can serve as a key strategy in cholera control and prevention.

In 2013, the World Health Organization (WHO) created a global stockpile of oral cholera vaccine (OCV) to ensure access to OCVs in outbreak and humanitarian emergency situations [2]. The three main contexts under which countries may request doses from the global OCV stockpile include 1) emergency use to control an active outbreak, 2) emergency use to prevent outbreaks during a humanitarian crisis, and 3) preventive use for areas deemed “hot-spots” or where cholera is endemic [3]. OCV is administered in two doses, given two weeks apart, and is much less effective in young children than in adults. Vaccine efficacy for two doses is 42% in those under five years old and 72% in those five years and older against clinical cholera [4]. For one dose, vaccine efficacy is reduced to 8% for those under five years old and 57.5% for those five years and older [5, 6]. However, protection from both vaccine and natural cholera infection wanes over time [710]. Children under five years old bear the greatest burden of cholera [11].

The standard approach to mass vaccination campaigns of OCV is untargeted and administers two doses [1215]. There remains, however, a global shortage of OCV. Countries have explored ways to maximize impact of limited vaccine supply. In April 2016 during the early stages of a cholera outbreak in Zambia, the Ministry of Health, in collaboration with Médicins sans Frontières (MSF) and the WHO, implemented a single-dose campaign as a way to stretch vaccine supply [16, 17]. Eight months later in December, a second dose was administered when there was more stock [17]. A single-dose approach was also used for cholera outbreaks in South Sudan in 2015 and was effective at preventing medically attended cholera during an outbreak [18]. A one-dose OCV campaign would vaccinate more people in exchange for a lower level of protection.

The optimal use of vaccine depends on many factors, such as the objectives of a vaccination program, the number of doses available, vaccine efficacy and a region’s local transmission dynamics. Local transmission dynamics may be influenced by region-specific patterns in migration, human mobility, and climate variability [1923].

In this study, we use mathematical models paired with optimization algorithms to determine the optimal vaccine allocation strategies during an active outbreak. We minimized three metrics of infection and disease burden: cumulative infections, cumulative symptomatic infections, and cumulative deaths. We explore the impact OCV could have had in outbreaks in Chad, Thailand, and Haiti—three distinct settings representing an urban area, a refugee camp, and a region torn by natural disaster respectively. For these settings each with distinct local transmission dynamics, minimizing each metric produced a different optimal vaccination strategy. We quantify the impact of these optimal strategies through these metrics.

Methods

Here we describe the methods we used for the study. We provide details of each outbreak setting. We describe the three mathematical models used per setting and highlight the distinctive features of each. These models were used to analyze how different settings can alter the optimal use of OCV following an outbreak. Next, we elaborate on the implementation of the vaccination campaign and the various vaccination strategies (including the optimal vaccine allocation strategy) we considered. We then describe the details of the optimization algorithm used to find the optimal vaccination strategy. Finally, we give details on the uncertainty analysis of our results.

Mathematical models of cholera transmission for different outbreak settings

Urban area: N’Djamena, Chad

Cholera has been present in Chad for decades [24]. In response to a large 2011 cholera epidemic in Chad, MSF worked closely with the Chadian Ministry of Health to try to limit the spread of the disease [25]. As part of that response, the MSF team and other health agencies collected case data in N’Djamena, the capital and largest city of Chad with a population of 993,500 in 2011, 19% of that are under five years old [25, 26]. It is unknown what triggered the epidemic, which resulted in 17,200 cases and 450 deaths, but it may be correlated with the occurrence of the rainy season [27, 28].

We constructed a transmission model with vaccination and two age groups: those below five years old, and those who are at least five years old. Susceptible (S) individuals are infected directly through contact with an infectious individual or indirectly through contact with contaminated water. They then become exposed but not yet infectious (E). After the latent period, they become infectious either with symptoms (I) or without symptoms (A). Eventually they recover (R) and are temporarily immune to infection until they become susceptible again. This model follows the general SEIRS framework, with two infectious compartments and a rainfall-modulated water reservoir (W) that tracks the concentration of V. cholerae (Fig 1A). We assume that asymptomatic infections are less infectious and shed less bacteria into the environment than symptomatic ones. Individuals may be unvaccinated or vaccinated with either one or two doses.

Fig 1. General framework of the models.

Fig 1

The three models share common epidemiological states: susceptible (S), exposed but not yet infectious (E), infectious with symptoms (I), infectious without symptoms (A), and recovered (R). Infectious individuals shed bacteria into the water (W) (dashed line). Unique features of each model are shown in thick arrows. A: N’Djamena, Chad, a densely populated city. Transmission is influenced by rainfall. B: Maela, a refugee camp. Individuals may enter and exit the population through in- and out-migration. C: Haiti, where transmission is influenced by a road and water mobility network. These networks connect the ten departments. The age-structured and vaccinated analogues of these epidemiological states are omitted for clarity. See S1 Appendix for details.

Using incidence data collected by MSF, we calibrated this model without age structure or vaccination to the 2011 epidemic in N’Djamena, Chad [29]. All parameters were fixed except for the direct transmission coefficient, environmental transmission coefficient, reporting ratio, and the number of recovered individuals at the start of the simulation. Details on the model calibration are found in S1 Appendix.

Maela refugee camp, Thailand

Between 2005 to 2012, surveillance had identified four cholera outbreaks in Maela, the largest refugee camp in Thailand with high population density and migration [12, 30]. The second largest of these outbreaks occurred in 2010 with 362 confirmed cases [31]. At this time, the camp was home to approximately 45,000 refugees, and 13% were children under five years old [12, 31].

We adapted a previously developed deterministic model of cholera transmission with two age groups that was calibrated to the 2010 epidemic in Maela to compare the impact of various vaccination campaigns [31]. In the original version of this model, individuals are either susceptible, infectious, or recovered (Fig 1B). They may be unvaccinated, once vaccinated, or twice vaccinated. We calibrated the two age groups (below five years old, and five years and older) to Maela demographics [12]. This model differs from the other two because individuals may enter and exit the population through births, in- and out-migration, and natural death.

A region torn by natural disaster: Haiti

Haiti comprises ten administrative departments, totaling 11 million inhabitants in 2010, with less than 12% under five years old [32]. In 2010 following a catastrophic earthquake, Haiti experienced its first recorded cholera outbreak in at least a century [33]. Poor access to water and sanitation in Haiti created a favorable condition for cholera to spread. Over the first two years of the epidemic, the Haitian Ministry of Public Health and Population reported more than 600,000 cases and over 7,000 deaths [34]. Since then, cholera has become endemic in Haiti [1].

We used a previously developed meta-population model of cholera transmission in Haiti. Each node in the model represents one of the ten administrative departments in Haiti [32]. The departments are connected through a river network and a road network, and within each department, individuals transition through a SEIR framework (Fig 1C). The road network was parameterized using a gravitational model and the river network was calibrated to Haiti’s hydrology (full details given in [32]). Like in the model for Chad, infections may occur with or without symptoms. Environmental transmission is modulated by a sinusoidal function that represents the dry and rainy season. The mobility network (both rivers and roads) distinguishes this model from the models for Chad and Maela.

Vaccination campaign

For each of the three models, we built and implemented a vaccination campaign that considered two age groups, those under five years old and those at least five years old. We considered a “leaky” vaccine that reduces the probability of infection upon exposure (reducing susceptibility) [35]. The vaccine effectiveness varied by age and by the number of doses received (S1 Table). Vaccine-induced immunity lasts an average of 4 years for two doses [7, 8], and 2 years for one dose [8]. As the duration of natural immunity lasts at least three years [9, 10], we assumed it to be equal to the duration of vaccine-induced immunity after two doses.

We explored counterfactual vaccination scenarios following cholera epidemics under varying levels of vaccination coverage, with enough vaccine to cover 10 to 100% of the population with a single dose (5 to 50% of the population with two doses). For each setting, we considered vaccination strategies that may allocate zero, one, or two doses to the different age groups (ages 0 to 4 years, and ages 5 years and older). The vaccination strategies considered include:

  1. no vaccination (baseline);

  2. two doses to individuals in both age groups allocated proportionally to their population (two-dose pro-rata, current standard);

  3. one dose to individuals in both age groups allocated proportionally to their population (one-dose pro-rata);

  4. two doses to children under five years old, and remaining doses allocated as one dose to individuals in the older group (mixed);

  5. one dose to individuals five years and older (one-dose-over-five);

  6. optimal allocation identified by our optimization routine (optimal).

We included the two-dose pro-rata strategy because this is the current standard, untargeted approach for mass OCV deployment worldwide [1215]. We evaluated each strategy over one and three years. For each time horizon, we measured the performance of each vaccination strategy on three different metrics of disease burden: cumulative infections, cumulative symptomatic infections, and cumulative deaths.

Vaccine doses were distributed in mass vaccination campaigns which took place over one week per round, with 14 days between doses [3]. We assumed that protection began immediately after a dose is received, so that those who are allocated two doses were protected by the first dose until they received their second dose. Vaccination campaigns in Chad and Maela began two weeks after the simulation started when 50 and 20 cumulative cases were diagnosed respectively, while in Haiti, vaccination began at the start of simulation with 7300 cumulative cases, consistent with the available surveillance incidence data [32].

Optimization

We applied optimization algorithms on the outcomes of our dynamic models of cholera transmission and vaccination for each setting to determine which vaccination strategy minimized disease metrics for each setting. We used a previously developed optimization routine [36, 37] that works in two steps: first, it performs an exhaustive grid search that allows us to explore the entire variable space within a 5% margin of vaccine allocation, followed by a heuristic global algorithm that uses the results from the grid search as initial conditions (description of the optimization routine can be found in S1 Appendix).

Uncertainty analysis

Once a solution was deemed optimal, we compared its performance to other strategies (the two-dose pro-rata, the one-dose pro-rata, mixed, and the one-dose-over-five). We examined the uncertainty in the metrics of disease burden (total infections, symptomatic infections, and deaths) arising from the uncertainty around the values of key model parameters. For these parameters, we sampled 1000 parameter sets from pre-determined distributions and recalculated the reductions in the metrics of disease burden. We report here the 95% uncertainty intervals (full details, including the parameters that were varied, can be found in S1 Appendix).

Results

Optimal vaccine allocation by metrics of disease burden

In the next sections, we provide results for a time horizon of one year. The optimal strategies that minimized cumulative infections, symptomatic infections, and deaths over one year were similar across Chad, Maela, and Haiti. When minimizing total and symptomatic infections, the optimal allocation strategies were largely identical in all three settings: Prioritize those at least five years old with a single dose of vaccine (Fig 2A, 2B, 2D, 2E, 2G and 2H). Once everyone in this group has received one dose, these optimal strategies allocated any remaining vaccine (above 80% vaccination coverage) differently by setting: i) in Chad, to those under five years old with two doses (Fig 2A and 2B); ii) in Haiti, as a second dose to those at least five years old (Fig 2G and 2H); and iii) in Maela, either of these strategies depending on whether total or symptomatic infections were minimized (Fig 2D and 2E). When minimizing deaths, the optimal strategies for Chad and Maela were the same as the ones which minimized symptomatic infections (Fig 2C and 2F). In contrast, in Haiti, the optimal strategy to minimize deaths prioritized the age groups in reverse order: Allocate two doses to children under five years old before distributing one dose to those at least five years old (Fig 2I).

Fig 2. Optimal vaccine allocation strategies to minimize total infections (left), symptomatic infections (center), or deaths (right) over one year.

Fig 2

A–C: Chad. D–F: Maela. G–I: Haiti. We considered enough vaccine to cover 10–100% of the population with a single dose.

As expected, reactive vaccination in an outbreak setting can substantially curtail the epidemic. Without vaccination the prevalence of cases peaked at 23, 60, and 179 cases per 100,000 for Chad, Maela, and Haiti respectively (Fig 3). Using the optimal strategies that minimized symptomatic infections (Fig 2B, 2E and 2H), vaccination lowered the peak prevalence the most in Maela (Fig 3B) and least in Haiti (Fig 3C). At 50% coverage, these optimal strategies lowered the peak prevalence (per 100,000) to 10 in Chad, 12 in Maela, and 133 in Haiti (reduction by 50%, 80%, and 26% respectively) (Fig 3). Next, we evaluated how the optimal strategies for each objective performed against other vaccination strategies as measured by the percentage averted for the three metrics of disease burden: total infections, symptomatic infections, and deaths.

Fig 3. Prevalence of cases per 100,000 over one year.

Fig 3

Prevalence of cases using an optimal vaccine allocation that minimized symptomatic infections over different vaccination coverage for A: Chad, B: Maela, and C: Haiti.

Performance of the optimal strategies in Chad, Maela, and Haiti

In Chad, the optimal strategies that minimized each metric of disease burden encompassed the one-dose-over-five strategy. These optimal strategies could have reduced up to 68% of total and symptomatic infections and 61% of deaths compared to no vaccination (Fig 4A, 4B and 4C). The optimal strategies minimizing total infections, symptomatic infections, and deaths maximally outperformed the two-dose pro-rata strategy at 80% coverage: by 23%, 23%, and 17% respectively. Compared to the one-dose pro-rata strategy, these optimal strategies averted up to 8% (at 80% coverage) more total and symptomatic infections and averted up to 6% (at 80% coverage) more deaths (Fig 4A, 4B and 4C).

Fig 4. Reductions in the metrics of disease burden from the vaccination campaigns over one year.

Fig 4

Percentage of total infections (left), symptomatic infections (center), and deaths (right) averted over one year for A–C: Chad, D–F: Maela, and G–I: Haiti. We considered enough vaccine to cover 10–100% of the population with a single dose.

In Maela, the optimal strategies to minimize each metric also encompassed the one-dose-over-five strategy, outperforming all other vaccination strategies (Fig 4D, 4E and 4F). These optimal strategies had larger reductions than the two-dose pro-rata strategy by up to 30% (and bigger than the one-dose pro-rata strategy by up to 8%). At 60% vaccination coverage, these optimal strategies had averted at least 75% of total infections, symptomatic infections, and deaths compared to no vaccination.

In Haiti, the optimal strategies reduced at most 36% of total and symptomatic infections and 31% of deaths (Fig 4G, 4H and 4I). The optimal strategies outperformed the two-dose pro-rata strategy by a small margin (up to 9% of total and symptomatic infections and 8% of deaths) and the one-dose pro-rata strategy by a smaller margin still (up to 3% of total and symptomatic infections and 6% deaths).

Our analysis suggests that optimal vaccination strategies will be most effective in Maela (with the highest percentage of total infections, symptomatic infections, and deaths averted), followed by Chad and Haiti (Fig 4). For example, at 80% vaccination coverage in Maela, Chad, and Haiti, the optimal strategies that minimized deaths averted 87%, 55%, and 25% of deaths, respectively (Fig 4C, 4F and 4I).

Comparison of the vaccination strategies across settings

The vaccination strategies that allocated a single dose of OCV outperformed the ones that allocated two doses for all three metrics and settings (Fig 4A, 4B, 4C, 4D, 4E, 4F, 4G and 4H), except for averted deaths in Haiti (Fig 4I). This suggests that the timing of the vaccination campaign plays a role in the optimal use of vaccine. When vaccination is started late, when many infections have already occurred (like in our scenario for Haiti) direct protection of those at highest risk with the most efficacious vaccine (two-dose strategies) is preferred. In contrast, when vaccination started early, vaccinating as many individuals as possible (single-dose strategies) to curtail transmission is better. Aside from the optimal strategy, the one-dose pro-rata strategy had the biggest impact with respect to all metrics (Fig 4A, 4B, 4C, 4D, 4E, 4F, 4G and 4H). The two-dose pro-rata strategy outperformed the mixed strategy at lower vaccination coverage, while the latter outperformed the former at higher coverage. This crossover occurred at between 30% to 60% vaccination coverage (Fig 4).

Comparing the pro-rata vaccination strategies, one-dose outperformed a two-dose allocation, irrespective of setting, metric of disease burden, and vaccination coverage. For example, for averted deaths, the one-dose pro-rata strategy outperformed the two-dose pro-rata strategy by up to 22%, 12%, and 2% of deaths in Maela, Chad, and Haiti respectively (Fig 4C, 4F and 4I). While this difference was large in settings where vaccination started early (Maela) it became insignificant in Haiti, where vaccination was assumed to start very late with respect to the epidemic curve, demonstrating that early vaccination is key to maximizing impact on reducing disease burden. Furthermore, in Maela and Chad, where vaccination started early in the epidemic when relatively fewer cases were diagnosed, vaccination prevented up to 90% and 61% of deaths respectively, compared to 28% in Haiti, where vaccination began later.

Short-term versus long-term impact

We investigated how the optimal strategies for each setting may change over a longer time horizon of 3 years. Recurring epidemics corresponded to seasonally forced transmission in both models for Chad and Haiti. In Maela, one case was re-seeded 1.5 years (chosen as halfway through the time horizon) after the first identified case.

Optimal strategies over a three year time horizon

When minimizing total and symptomatic infections, the optimal strategies in Maela, Chad, and Haiti all prioritized individuals at least five years old (Fig 5A, 5B, 5D, 5E, 5G and 5H). In Maela and Chad, this age group was allocated a single dose when vaccine supply was low (below 40% vaccination coverage) and a mix of one and two doses with higher vaccine supply (Fig 5A, 5B, 5D and 5E). In Haiti, the optimal strategies allocated two doses to those at least five years old regardless of vaccine availability (Fig 5G and 5H).

Fig 5. Optimal vaccine allocation strategies to minimize total infections (left), symptomatic infections (center), and deaths (right) over three years.

Fig 5

A–C: Chad. D–F: Maela. G–I: Haiti. We considered enough vaccine to cover 10–100% of the population with a single dose.

When the objective was to minimize deaths over three years, the optimal strategies varied across Chad, Maela, and Haiti. In Chad, the optimal strategy was similar to the mixed strategy, prioritizing children under five years old with mostly two doses for all vaccination coverage. Once these children were vaccinated (above 30% vaccination coverage), the optimal strategy allocated the remaining vaccine to those at least five years old with a mix of one and two doses (Fig 5C). In Haiti, the optimal strategy first targeted children under five years old with mostly two doses before allocating two doses to those at least five years old with any remaining vaccine (Fig 5I). In Maela, the optimal strategy prioritized the age group at least five years old with one dose (below 60% vaccination coverage) and with two doses (60% coverage and above), and allocated some vaccine to children under five years old (40% to 70% coverage) (Fig 5F).

Performance of vaccination strategies over three years

While the absolute impact was larger over three years than one year, the impact of the vaccination strategies relative to no vaccination, measured by percentage of infections and deaths averted, was smaller at three years than at one year (Fig 6). In Maela, the re-introduced case did not produce any additional outbreaks, whereas there were multiple epidemic waves in Chad and Haiti. Across the settings, vaccination strategies over the longer term had the biggest impact in Maela, followed by Chad and Haiti (same order as over the shorter term).

Fig 6. Reductions in metrics of disease burden from the vaccination campaigns over three years.

Fig 6

Percentage of total infections (left), symptomatic infections (center), and deaths (right) averted over three years for A–C: Chad, D–F: Maela, and G–I: Haiti. We considered enough vaccine to cover 10–100% of the population with a single dose.

The performance differences between vaccination strategies over three years were smaller compared to those over one year. When minimizing transmission (total and symptomatic infections) over three years, the optimal strategies maximally outperformed the other strategies (at 100% vaccination coverage) by 8% in Chad (Fig 6A and 6B), 14% in Maela (Fig 6D and 6E), and 2% in Haiti (Fig 6G and 6H). When minimizing deaths, the optimal strategy at 80% vaccination coverage for Chad, Maela, and Haiti averted 25%, 56%, and 10% of deaths respectively (Fig 6C, 6F and 6I). At this vaccination coverage, the differences in deaths averted between the highest (optimal) and lowest (one-dose pro-rata) performing strategies were 8% in Chad, 13% in Maela, and 3% in Haiti. Over the longer term, the one-dose pro-rata strategy did not always outperform the two-dose pro-rata strategy. This is expected, as protection from a single dose was assumed to wane after two years (compared to four years of protection from two doses).

The optimal strategies over one and three years indicate that it is best to allocate one dose under limited vaccine supply in an outbreak setting for the highest reductions in disease and deaths over the short-term. However, when more vaccine is available later, a second dose can be allocated to prevent further outbreaks.

A vaccine that reduces the likelihood of symptoms upon infection

In this section, we investigated how the optimal strategies may change if a vaccine reduced the likelihood of having symptoms upon infection (disease-reducing) instead of one that reduced susceptibility to infection. We illustrate the results with the model calibrated for Chad.

Optimal vaccination strategies

Over one year, the optimal strategies that minimized total infections, symptomatic infections, and deaths were the same for both vaccines (S1 Fig), prioritizing a single dose to those at least five years old before allocating two doses to the younger age group. Over three years, the optimal strategies for each objective using a disease-reducing vaccine were slightly different to those using a susceptibility-reducing vaccine. When minimizing transmission (total or symptomatic infections), the optimal strategies for both vaccines prioritized a single dose to those at least five years old. For the disease-reducing vaccine, a second dose was allocated to the same group when coverage exceeded 70% (S2(A) and S2(B) Fig), whereas for the susceptibility-reducing vaccine, it was allocated sooner (above 30% coverage) (Fig 5A and 5B). When minimizing deaths, the optimal strategies prioritized two doses to children under five years old for both vaccines (S2(C) Fig and Fig 2C). Any remaining vaccines were allocated to those at least five years old as a single dose (with the disease-reducing vaccine) or as a mix of one and two doses (susceptibility-reducing vaccine).

Comparison of optimal strategies using two different vaccines

Here we compare the performance of the optimal strategies using the two different vaccines. Not surprisingly, the susceptibility-reducing vaccine outperformed the disease-reducing vaccine when minimizing total infections by up to 23% and 19% over one and three years respectively (Fig 4A, S3(A) Fig, Fig 6A, and S4(A) Fig). When minimizing symptomatic infections and deaths, however, the optimal strategies using a disease-reducing vaccine outperformed ones using a susceptibility-reducing vaccine by up to 2% over one year and 12% over three years (Fig 4B and 4C, S3(B) and S3(C) Fig, Fig 6B and 6C, S4(B) and S4(C) Fig).

Comparison of optimal strategies to other vaccination strategies

Here we compare the optimal strategies using the disease-reducing vaccine with other vaccination strategies. There was no qualitative difference in the performance ranking among the various vaccination strategies over one year between the two vaccines. The one-dose strategies still broadly outperformed two-dose strategies for all metrics of disease burden over one year and for averting total and symptomatic infections over three years (S3 and S4 Figs). The differences in performance between the strategies with the highest and lowest reductions for total infections, symptomatic infections, and deaths were up to 17%, 24%, and 17% over one year respectively (or 4%, 11%, and 10% over three years respectively) (S3 and S4 Figs).

Discussion

We paired mathematical models of cholera transmission and vaccination with optimization algorithms to determine the optimal vaccination strategies and their impact on various metrics of disease burden. We explored vaccination campaigns that included the use of one dose of OCV, which is half of the recommended two-dose regimen. We considered two target populations by age (under five years old, and five years and older), different levels of vaccination coverage, three distinct cholera outbreak settings, and a time horizon of one and three years. We compared these optimal strategies to other vaccination strategies.

We found that, over the short term, strategies allocating one dose of vaccine to those five years and older reduced the most cumulative infections, symptomatic infections, and deaths for all three outbreak settings in Chad, Maela, and Haiti. In Haiti, the optimal allocation strategies also fully protected children under five years old with two doses to minimize deaths. Our results suggest that over a shorter term (one year), strategies with a one-dose allocation to those aged five years and older, for whom one dose of vaccine is more effective, outperform those allocating two doses irrespective of setting, metric of disease burden, and vaccination coverage. Further, our results show that if reactive vaccination campaigns start late with respect to the epidemic curve, when there are already a significant number of cases (Haiti in our settings) then it is still optimal to give one dose to those aged five years and older, but to also give full protection to the youngest children. This would stretch the vaccine supply considerably, and of course, once vaccine supply is replenished, vaccination campaigns with a second dose for long-term protection are desired.

A modeling study has found that a one-dose vaccination campaign would avert 1.1 to 1.2 times as many cases and deaths as a two-dose campaign in an outbreak setting over the short term [38]. This is consistent with our finding that optimal strategies for each objective, which allocated a mix of one and two doses, would avert up to 1.2 to 1.8 times as many cases and deaths as a two-dose pro-rata strategy over the course of one year. Similarly, the one-dose pro-rata strategy would avert 1.08 to 1.5 times as many cases and deaths as the two-dose pro-rata strategy across the three outbreak settings. Different to their study, we used two age groups and age-specific case fatality rates. In particular, we assumed that the case fatality rates for children under five years old were about 5 times higher than individuals who were older [39]. Another modeling study analyzed the impact of vaccination campaign timing and one-dose vaccine effectiveness and found that timing had a bigger impact on case counts than one-dose effectiveness [31]. This is consistent with our finding that the impact of vaccination was smallest in Haiti, where vaccination began later during the exponential phase of the epidemic.

Our results of the optimal use of OCV are consistent with previous studies for other infectious diseases that have demonstrated that the optimal use of vaccine depends on coverage, vaccine efficacy and the timing of vaccination with respect to the epidemic curve, favoring direct protection of high-risk groups if vaccination starts too late [4042]. However, the procurement and deployment of OCV usually include significant delays. There is a median delay of three months between the declaration of an emergency and the start of the first round of vaccination [3]. Delay times range widely—the time from the first laboratory confirmation of cholera (or occurrence of humanitarian emergency) to the receipt of the official OCV request spans between 12 and 206 days [3]. These delays in vaccine shipment may result in campaigns starting after the outbreak is over [43]. Further, our results are in line with previous modeling that explored the optimal use of vaccine when multiple doses are required for other pathogens, finding that fractional strategies are optimal when the protection afforded by a lower-than-recommended dose is sufficiently high [37, 4446]. Besides cholera, other diarrheal diseases pose significant burden. In 2016, rotavirus infection caused more than 258 million episodes of diarrhea among children under five years old globally [47]. Rotavirus vaccines are also delivered in multiple doses, and some studies have suggested that an incomplete series of the rotavirus vaccine may provide sufficient protection against severe disease and hospitalizations [4850]. It is important to consider that the optimal allocation of vaccine may change under different epidemiological contexts. In the present work we showed the optimal allocation of OCV under the context of emergency use to control an active outbreak (in epidemic situations). However, cholera outbreaks range widely depending on the region (short outbreaks are commonly seen in Africa while cholera is endemic in Bangladesh), and the optimal vaccine allocation may be different if used to prevent outbreaks or in endemic areas with hot spots.

The similar optimal vaccination strategies across three different settings and under varying degrees of coverage provide reassurance that these results are robust to a range of transmission dynamics. However, there are limitations to our work. As with all mathematical models, our models have simplifying assumptions on the true transmission dynamics and use parameter values that are subject to some uncertainty. In particular, we assumed homogeneity in mixing patterns and probability of a symptomatic case given infection. We calibrated the Chad model to incidence data. However, the burden of cholera is under-reported [51, 52]. Countries may suppress reports of cholera cases due to the perceived influence cholera has on tourism and export industries [53]. Additionally, the WHO case definition for cholera currently excludes children under five years old [54]. This exclusion can further obscure the true burden of cholera, especially in areas where children face increased cholera incidence. Importantly, the case fatality ratio for cholera differs by age and geography. We assumed a fixed multiplier that increased childhood mortality. In reality, this multiplier is likely to change for different regions with different healthcare systems and access to clean water. Further studies are needed to truly evaluate the burden of cholera in young children. In particular, serological studies [55] might be useful to determine the burden of different diarrheal diseases in a particular region. We did not consider other possible confounders (e.g., differences in waning immunity and pre-existing immunity in endemic versus epidemic settings, the use of other interventions in tandem with vaccination) which could affect the population impact of vaccination.

There is some uncertainty around the vaccine efficacy of one dose of OCV. Trials of one-dose vaccine efficacy of OCV have demonstrated good protection for individuals over five years old, and low to no protection for children below five years old in Bangladesh where cholera is endemic [5, 6]. One-dose vaccine effectiveness from case-control; test-negative, case-control; and case-cohort studies ranges widely from 33% to 87%, and some of these estimates were not statistically significant [13, 18, 56, 57]. Understanding how that protection translates to different settings, such as in Haiti where cholera is newly endemic, should be a priority. We also made a simplifying assumption in our models that all children under five years old were eligible to be vaccinated. In reality, the vaccine is not approved for children under one year old.

Despite the counterfactual nature of our vaccination campaigns, our results can provide a basis for future cholera outbreaks, especially under settings with poor water infrastructure and constrained resources. We explored hypothetical vaccination campaigns that took place two weeks after the first case was identified (Chad and Maela) and during the exponential phase of the epidemic (Haiti). In reality, in emergency situations, the time from vaccine request to vaccine delivery are often long [3]. In emergency situations, the median time between the first laboratory confirmation (or occurrence of a humanitarian emergency) to one week after the first round of vaccination when immunity develops was 66 days [3]. Our results point to the need to reduce these lag times in order to increase the impact of vaccination campaigns. A one-dose vaccine allocation would reduce this logistical hurdle, and it would not preclude a second dose once there is more vaccine supply. However, in places where there is a lot of population migration, a long interval between the first and the second dose might result in having a proportion of the population receiving only one dose. In the event that the risk of future epidemics persist, recurrent vaccination campaigns may be required to maintain protection over time.

Supporting information

S1 Appendix. Appendix: The mathematical models.

(PDF)

S1 Fig. Optimal vaccine allocation strategies for different goals in Chad over one year using a vaccine that reduces the probability of symptoms upon infection.

A: total infections. B: symptomatic infections. C: deaths. We considered enough vaccine to cover 10–100% of the population with a single dose.

(TIF)

S2 Fig. Optimal vaccine allocation strategies for different goals in Chad over three years using a vaccine that reduces the probability of symptoms upon infection.

A: total infections. B: symptomatic infections. C: deaths. We considered enough vaccine to cover 10–100% of the population with a single dose.

(TIF)

S3 Fig. Reductions in metrics of disease burden from vaccination campaigns in Chad over one year with a vaccine that reduces the probability of symptoms upon infection.

We considered enough vaccine to cover 10–100% of the population with a single dose.

(TIF)

S4 Fig. Reductions in metrics of disease burden from vaccination campaigns in Chad over three years with a vaccine that reduces the probability of symptoms upon infection.

We considered enough vaccine to cover 10–100% of the population with a single dose.

(TIF)

S1 Table. Description of parameters related to the vaccine and disease metrics.

(PDF)

Acknowledgments

We thank Joshua Havumaki, Rafael Reza, Marisa Eisenberg, and Andrew Azman for providing access to research-related materials that were key to our analysis. We thank Dobromir Dimitrov for his helpful feedback on the manuscript.

Data Availability

All relevant data are within the manuscript and its Supporting information files.

Funding Statement

TL and LM acknowledge support from the UK Foreign, Commonwealth and Development Office and Wellcome [grant number 215685/Z/19/Z]. The Scientific Computing Infrastructure at Fred Hutch was supported by the National Institutes of Health ORIP grant S10OD028685. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1. Ali M, Nelson AR, Lopez AL, Sack DA. Updated global burden of cholera in endemic countries. PLOS Neglected Tropical Diseases. 2015;9(6):1–13. doi: 10.1371/journal.pntd.0003832 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. World Health Organization. Cholera vaccines: WHO position paper—August 2017. Weekly Epidemiological Record. 2017;92(34):477–498.28845659 [Google Scholar]
  • 3. Pezzoli L. Global oral cholera vaccine use, 2013–2018. Vaccine. 2020;38:A132–A140. Available from: 10.1016/j.vaccine.2019.08.086. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Bhattacharya SK, Sur D, Ali M, Kanungo S, You YA, Manna B, et al. 5 year efficacy of a bivalent killed whole-cell oral cholera vaccine in Kolkata, India: A cluster-randomised, double-blind, placebo-controlled trial. The Lancet Infectious Diseases. 2013;13(12):1050–1056. doi: 10.1016/S1473-3099(13)70273-1 [DOI] [PubMed] [Google Scholar]
  • 5. Qadri F, Wierzba TF, Ali M, Chowdhury F, Khan AI, Saha A, et al. Efficacy of a single-dose, inactivated oral cholera vaccine in Bangladesh. New England Journal of Medicine. 2016;374(18):1723–1732. doi: 10.1056/NEJMoa1510330 [DOI] [PubMed] [Google Scholar]
  • 6. Qadri F, Ali M, Lynch J, Chowdhury F, Khan AI, Wierzba TF, et al. Efficacy of a single-dose regimen of inactivated whole-cell oral cholera vaccine: results from 2 years of follow-up of a randomised trial. The Lancet Infectious Diseases. 2018;18(6):666–674. Available from: 10.1016/S1473-3099(18)30108-7. [DOI] [PubMed] [Google Scholar]
  • 7. Bi Q, Ferreras E, Pezzoli L, Legros D, Ivers LC, Date K, et al. Protection against cholera from killed whole-cell oral cholera vaccines: A systematic review and meta-analysis. The Lancet Infectious Diseases. 2017;17(10):1080–1088. doi: 10.1016/S1473-3099(17)30359-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Franke MF, Ternier R, Jerome JG, Matias WR, Harris JB, Ivers LC. Long-term effectiveness of one and two doses of a killed, bivalent, whole-cell oral cholera vaccine in Haiti: an extended case-control study. The Lancet Global Health. 2018;6(9):e1028–e1035. Available from: 10.1016/S2214-109X(18)30284-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Ali M, Emch M, Park JK, Yunus M, Clemens J. Natural cholera infection-derived immunity in an endemic setting. Journal of Infectious Diseases. 2011;204(6):912–918. doi: 10.1093/infdis/jir416 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Leung T, Matrajt L. Protection afforded by previous Vibrio cholerae infection against subsequent disease and infection: A review. PLOS Neglected Tropical Diseases. 2021;15(5):e0009383. Available from: 10.1371/journal.pntd.0009383. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Deen JL, von Seidlein L, Sur D, Agtini M, Lucas MES, Lopez L, et al. The high burden of cholera in children: Comparison of incidence from endemic areas in Asia and Africa. PLoS Neglected Tropical Diseases. 2008;2(2). doi: 10.1371/journal.pntd.0000173 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Phares CR, Date K, Travers P, Déglise C, Wongjindanon N, Ortega L, et al. Mass vaccination with a two-dose oral cholera vaccine in a long-standing refugee camp, Thailand. Vaccine. 2016;34(1):128–133. doi: 10.1016/j.vaccine.2015.10.112 [DOI] [PubMed] [Google Scholar]
  • 13. Khatib AM, Ali M, von Seidlein L, Kim DR, Hashim R, Reyburn R, et al. Effectiveness of an oral cholera vaccine in Zanzibar: Findings from a mass vaccination campaign and observational cohort study. The Lancet Infectious Diseases. 2012;12(11):837–844. Available from: 10.1016/S1473-3099(12)70196-2. [DOI] [PubMed] [Google Scholar]
  • 14. Lucas MES, Deen JL, von Seidlein L, Wang XY, Ampuero J, Puri M, et al. Effectiveness of mass oral cholera vaccination in Beira, Mozambique. The New England Journal of Medicine. 2005;352(8):757–767. doi: 10.1056/NEJMoa043323 [DOI] [PubMed] [Google Scholar]
  • 15. Lubogo M, Mohamed AM, Ali AH, Ali AH, Popal GR, Kiongo D, et al. Oral cholera vaccination coverage in an acute emergency setting in Somalia, 2017. Vaccine. 2020;38(October 2017):A141–A147. Available from: 10.1016/j.vaccine.2020.01.015. [DOI] [PubMed] [Google Scholar]
  • 16. Ferreras E, Chizema-Kawesha E, Blake A, Chewe O, Mwaba J, Zulu G, et al. Single-dose cholera vaccine in response to an outbreak in Zambia. The New England Journal of Medicine. 2018;378(6):578–579. doi: 10.1056/NEJMc1711583 [DOI] [PubMed] [Google Scholar]
  • 17. Poncin M, Zulu G, Voute C, Ferreras E, Muleya CM, Malama K, et al. Implementation research: Reactive mass vaccination with single-dose oral cholera vaccine, Zambia. Bulletin of the World Health Organization. 2018;96(2):86–93. doi: 10.2471/BLT.16.189241 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Azman AS, Parker LA, Rumunu J, Tadesse F, Grandesso F, Deng LL, et al. Effectiveness of one dose of oral cholera vaccine in response to an outbreak: a case-cohort study. The Lancet Global Health. 2016;4(11):e856–e863. Available from: 10.1016/S2214-109X(16)30211-X. [DOI] [PubMed] [Google Scholar]
  • 19. Peak CM, Reilly AL, Azman AS, Buckee CO. Prolonging herd immunity to cholera via vaccination: Accounting for human mobility and waning vaccine effects. PLOS Neglected Tropical Diseases. 2018;12(2):1–18. doi: 10.1371/journal.pntd.0006257 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Desai AN, Ramatowski JW, Marano N, Madoff LC, Lassmann B. Infectious disease outbreaks among forcibly displaced persons: An analysis of ProMED reports 1996-2016. Conflict and Health. 2020;14(1):1–10. doi: 10.1186/s13031-020-00295-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Castelli F, Sulis G. Migration and infectious diseases. Clinical Microbiology and Infection. 2017;23(5):283–289. Available from: 10.1016/j.cmi.2017.03.012. [DOI] [PubMed] [Google Scholar]
  • 22. Koelle K, Rodó X, Pascual M, Yunus M, Mostafa G. Refractory periods and climate forcing in cholera dynamics. Nature. 2005;436(7051):696–700. doi: 10.1038/nature03820 [DOI] [PubMed] [Google Scholar]
  • 23. Moore SM, Azman AS, Zaitchik BF, Mintz ED, Brunkard J, Legros D, et al. El Niño and the shifting geography of cholera in Africa. Proceedings of the National Academy of Sciences of the United States of America. 2017;114(17):4436–4441. doi: 10.1073/pnas.1617218114 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Mengel MA, Delrieu I, Heyerdahl L, Gessner BD. Cholera outbreaks in Africa. Current Topics in Microbiology and Immunology. 2014;379(1):117–144. [DOI] [PubMed] [Google Scholar]
  • 25. Azman AS, Luquero FJ, Salje H, Mbaïbardoum NN, Adalbert N, Ali M, et al. Micro-hotspots of risk in urban cholera epidemics. Journal of Infectious Diseases. 2018;218(7):1164–1168. doi: 10.1093/infdis/jiy283 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Population Pyramid. Population of Chad 2011; 2021. Available from: https://www.populationpyramid.net/chad/2011/.
  • 27. Piarroux R, Faucher B. Cholera epidemics in 2010: Respective roles of environment, strain changes, and human-driven dissemination. Clinical Microbiology and Infection. 2012;18(3):231–238. doi: 10.1111/j.1469-0691.2012.03763.x [DOI] [PubMed] [Google Scholar]
  • 28.Médecins Sans Frontières. Chad—Preventing another cholera epidemic; 2012. Available from: https://www.msf.org/chad-preventing-another-cholera-epidemic.
  • 29. Finger F, Bertuzzo E, Luquero FJ, Naibei N, Touré B, Allan M, et al. The potential impact of case-area targeted interventions in response to cholera outbreaks: A modeling study. PLoS Medicine. 2018;15(2):1–27. doi: 10.1371/journal.pmed.1002509 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Scobie HM, Phares CR, Wannemuehler KA, Nyangoma E, Taylor EM, Fulton A, et al. Use of oral cholera vaccine and knowledge, attitudes, and practices regarding safe water, sanitation and hygiene in a long-standing refugee camp, Thailand, 2012-2014. PLoS Neglected Tropical Diseases. 2016;10(12):2012–2014. doi: 10.1371/journal.pntd.0005210 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Havumaki J, Meza R, Phares CR, Date K, Eisenberg MC. Comparing alternative cholera vaccination strategies in Maela refugee camp: Using a transmission model in public health practice. BMC Infectious Diseases. 2019;19(1):1–17. doi: 10.1186/s12879-019-4688-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Lee EC, Chao DL, Lemaitre J, Matrajt L, Pasetto D, Perez-Saez J, et al. Achieving coordinated national immunity and cholera elimination in Haiti through vaccination. Lancet Global Health. 2020;8:e1081–1089. doi: 10.1016/S2214-109X(20)30310-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Walton DA, Ivers LC. Responding to cholera in post-earthquake Haiti. New England Journal of Medicine. 2011;364(1):3–5. doi: 10.1056/NEJMp1012997 [DOI] [PubMed] [Google Scholar]
  • 34. Barzilay EJ, Schaad N, Magloire R, Mung KS, Boncy J, Dahourou GA, et al. Cholera surveillance during the Haiti epidemic — The first 2 years. New England Journal of Medicine. 2013;368(7):599–609. doi: 10.1056/NEJMoa1204927 [DOI] [PubMed] [Google Scholar]
  • 35. Halloran ME, Haber M, Ira M Longini J, Struchiner CJ. Direct and indirect effects in vaccine efficacy and effectiveness. American Journal of Epidemiology. 1991;133(October):323–331. doi: 10.1093/oxfordjournals.aje.a115884 [DOI] [PubMed] [Google Scholar]
  • 36. Matrajt L, Eaton J, Leung T, Brown ER. Vaccine optimization for COVID-19: Who to vaccinate first? Science Advances. 2021;7(6):eabf1374. Available from: http://advances.sciencemag.org/content/7/6/eabf1374. doi: 10.1126/sciadv.abf1374 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Matrajt L, Eaton J, Leung T, Dimitrov D, Schiffer JT, Swan DA, et al. Optimizing vaccine allocation for COVID-19 vaccines shows the potential role of single-dose vaccination. Nature Communications. 2021;12 (3449). Available from: 10.1038/s41467-021-23761-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Azman AS, Luquero FJ, Ciglenecki I, Grais RF, Sack DA, Lessler J. The impact of a one-dose versus two-dose oral cholera vaccine regimen in outbreak settings: A modeling study. PLoS Medicine. 2015;12(8):e1001867. doi: 10.1371/journal.pmed.1001867 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Troeger C, Blacker BF, Khalil IA, Rao PC, Cao S, Zimsen SR, et al. Estimates of the global, regional, and national morbidity, mortality, and aetiologies of diarrhoea in 195 countries: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Infectious Diseases. 2018;18(11):1211–1228. doi: 10.1016/S1473-3099(18)30362-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Matrajt L, Longini IM. Optimizing vaccine allocation at different points in time during an epidemic. PLoS ONE. 2010;5(11). doi: 10.1371/journal.pone.0013767 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Medlock J, Galvani AP. Optimizing influenza vaccine distribution. Science. 2009;325(5948):1705–1708. Available from: http://www.sciencemag.org/cgi/doi/10.1126/science.1175570. [DOI] [PubMed] [Google Scholar]
  • 42. Mylius SD, Hagenaars TJ, Lugnér AK, Wallinga J. Optimal allocation of pandemic influenza vaccine depends on age, risk and timing. Vaccine. 2008;26(29-30):3742–3749. doi: 10.1016/j.vaccine.2008.04.043 [DOI] [PubMed] [Google Scholar]
  • 43. Bwire G, Orach CG, Aceng FL, Arianitwe SE, Matseketse D, Tumusherure E, et al. Refugee Settlements and Cholera Risks in Uganda, 2016—2019. The American Journal of Tropical Medicine and Hygiene. 2021:1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Matrajt L, Britton T, Halloran ME, Longini IM. One versus two doses: What is the best use of vaccine in an influenza pandemic? Epidemics. 2015;13:17–27. Available from: 10.1016/j.epidem.2015.06.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Riley S, Wu JT, Leung GM. Optimizing the dose of pre-pandemic influenza vaccines to reduce the infection attack rate. PLoS Medicine. 2007;4(6):1032–1040. doi: 10.1371/journal.pmed.0040218 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Wood J, McCaw J, Becker N, Nolan T, MacIntyre CR. Optimal dosing and dynamic distribution of vaccines in an influenza pandemic. American Journal of Epidemiology. 2009;169(12):1517–1524. doi: 10.1093/aje/kwp072 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Troeger C, Khalil IA, Rao PC, Cao S, Blacker BF, Ahmed T, et al. Rotavirus vaccination and the global burden of rotavirus diarrhea among children younger than 5 years. JAMA Pediatrics. 2018;172(10):958–965. doi: 10.1001/jamapediatrics.2018.1960 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Gheorghita S, Birca L, Donos A, Wasley A, Birca I, Cojocaru R, et al. Impact of rotavirus vaccine introduction and vaccine effectiveness in the Republic of Moldova. Clinical Infectious Diseases. 2016;62(S2):S140–S146. doi: 10.1093/cid/civ1209 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Pringle KD, Patzi M, Tate JE, Iniguez Rojas V, Patel M, Inchauste Jordan L, et al. Sustained effectiveness of rotavirus vaccine against very severe rotavirus disease through the second year of life, Bolivia 2013-2014. Clinical Infectious Diseases. 2016;62(S2):S115–S120. doi: 10.1093/cid/civ1026 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Willame C, Noordegraaf-Schouten MV, Gvozdenović E, Kochems K, Oordt-Speets A, Praet N, et al. Effectiveness of the oral human attenuated rotavirus vaccine: A systematic review and meta-analysis–2006-2016. Open Forum Infectious Diseases. 2018;5(11):1–10. doi: 10.1093/ofid/ofy292 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51. Deen J, Mengel MA, Clemens JD. Epidemiology of cholera. Vaccine. 2020;38:A31–A40. doi: 10.1016/j.vaccine.2019.07.078 [DOI] [PubMed] [Google Scholar]
  • 52. Kanungo S, Sah BK, Lopez AL, Sung JS, Paisley AM, Sur D, et al. Cholera in India: An analysis of reports, 1997-2006. Bulletin of the World Health Organization. 2010;88(3):185–191. doi: 10.2471/BLT.09.073460 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. Legros D. Global cholera epidemiology: Opportunities to reduce the burden of cholera by 2030. Journal of Infectious Diseases. 2018;218(Suppl 3):S137–S140. doi: 10.1093/infdis/jiy486 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.WHO Global Task Force on Cholera Control. Cholera outbreak: assessing the outbreak response and improving preparedness; 2004. Available from: https://apps.who.int/iris/handle/10665/43017.
  • 55. Azman AS, Lessler J, Luquero FJ, Bhuiyan TR, Khan AI, Chowdhury F, et al. Estimating cholera incidence with cross-sectional serology. Science Translational Medicine. 2019;11(480). doi: 10.1126/scitranslmed.aau6242 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56. Ivers LC, Hilaire IJ, Teng JE, Almazor CP, Jerome JG, Ternier R, et al. Effectiveness of reactive oral cholera vaccination in rural Haiti: A case-control study and bias-indicator analysis. The Lancet Global Health. 2015;3(3):e162–e168. Available from: 10.1016/S2214-109X(14)70368-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Wierzba TF, Kar SK, Mogasale VV, Kerketta AS, You YA, Baral P, et al. Effectiveness of an oral cholera vaccine campaign to prevent clinically-significant cholera in Odisha State, India. Vaccine. 2015;33(21):2463–2469. Available from: 10.1016/j.vaccine.2015.03.073. [DOI] [PubMed] [Google Scholar]
PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0010358.r001

Decision Letter 0

Sharon M Tennant, James Michael Fleckenstein

15 Feb 2022

Dear Dr. Matrajt,

Thank you very much for submitting your manuscript "Optimizing one-dose and two-dose cholera vaccine allocation in outbreak settings: A modeling study" for consideration at PLOS Neglected Tropical Diseases. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

Your manuscript has been reviewed by experts in cholera vaccinology. Each of the reviewers has requested some minor revisions to help clarify the methodology and some additional discussion regarding the limitations of the analyses presented. Their comments are appended here (comments from Reviewer #1 are shown below and comments from Reviewer #2 are attached). Please give their feedback careful consideration in drafting a revised manuscript.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

James Michael Fleckenstein, M.D.

Associate Editor

PLOS Neglected Tropical Diseases

Sharon Tennant

Deputy Editor

PLOS Neglected Tropical Diseases

***********************

Your manuscript has been reviewed by experts in cholera vaccinology. Each of the reviewers has requested some minor revisions to help clarify the methodology and some additional discussion regarding the limitations of the analyses presented. Their comments are appended here. Please give their feedback careful consideration in drafting a revised manuscript.

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: The methods are clearly described.

Reviewer #2: (No Response)

--------------------

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: yes, the analysis matches the plan

The figures need to better label the x and y axes.

Reviewer #2: (No Response)

--------------------

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: The conclusions are supported by the data, however, the epidemiological patterns included in this analysis seem to assume these patterns cover the most common patterns. Unfortunately, cholera outbreaks run a large gamut of patterns from very brief outbreaks seen most commonly in Africa to the nearly continuous endemic pattern seen in Bangladesh. Thus, additional limitations of their model need to be described.

Reviewer #2: (No Response)

--------------------

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: Minor revisions

Reviewer #2: (No Response)

--------------------

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: Optimizing one-dose and two-dose cholera vaccine allocation in outbreak settings: A modeling study.

This is an elegant modeling study evaluating different dosing strategies for using oral cholera vaccine. They use the cholera epidemiological patterns from three geographic areas in an attempt to capture different patterns in the different regions. These three areas have cholera patterns that are quite unique. I am assuming that other reviewers who are more skilled in modeling methods will provide additional review of the actual modeling mathematics, so my review will mainly deal with comments on how this model may be used for decision making.

It appears that the findings are quite consistent with earlier publications, especially “Azman AS, et al. The impact of a one-dose versus two-dose oral cholera vaccine regimen in outbreak settings: A modeling study. PLoS Medicine. 2015;12(8):e1001867.” This article which is cited previously concluded that a single dose strategy provides significant public heath benefit compared to two doses when the number of vaccine doses is limited in an outbreak situation, but it did not deal with more prolonged outbreaks or endemic situations which this new manuscript attempts to include.

The authors correctly point out that rapid deployment of vaccine is key to a successful vaccine campaign during outbreaks. Unfortunately, when attempting to vaccinate quickly, the current procedures for obtaining vaccine from a central global stockpile, even though being designed to be rapid, in fact often result in vaccinations beginning delivered well after the peak of the outbreak and sometimes even after the outbreak is over (see “Bwire G, et al. Use of surveys to evaluate an integrated oral cholera vaccine campaign in response to a cholera outbreak in Hoima district, Uganda. BMJ Open 2020, 10:e038464”. It would seem that, although the authors do stress this aspect, the role of delays in vaccination might be stressed even more and a sensitivity analysis to account for delays would be valuable.

The authors should describe the three mechanisms for accessing OCV from the global stockpile. These include 1) emergency use to control outbreaks, 2) emergency use to prevent outbreaks during a humanitarian crisis, and 3) preventive use of vaccine for areas determined to be hot-spots. It is not clear which of these situations apply to their model and the manuscript would benefit from aligning their model with these three.

For example, if one is using the vaccine for the emergency control of an outbreak, most outbreaks occur suddenly, and are of relatively short duration so nearly all the benefit occurs in the first year. Another outbreak may not occur for several years so determining a benefit over three years would show little impact relative to a one year impact and providing a second dose to this area will increase costs but provide little additional benefit. This would change of course, if this same area was also previously determined to be a hot-spot. (Outbreaks are more likely to occur in such hot-spots.)

If the campaign is intending to vaccinate a “hot-spot” where outbreaks occur frequently, the second dose could more readily demonstrate additional benefit. Both of these situations are also then different from the endemic situation in Bangladesh where cholera occurs continuously at predicable rates. Obviously, a model cannot consider every possible scenario, but the discussion could provide additional context for these different situations.

A specific queries and suggestions.

For the age group <5, did the model assume that all children under age 5 would be vaccinated or only the age group >1 year. (The vaccine is not approved for children <1 year).

Reviewer #2: (No Response)

--------------------

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

References

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article's retracted status in the References list and also include a citation and full reference for the retraction notice.

Attachment

Submitted filename: PNTD_Reviewer_Comment.docx

PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0010358.r003

Decision Letter 1

Sharon M Tennant, James Michael Fleckenstein

25 Mar 2022

Dear Dr. Matrajt,

We are pleased to inform you that your manuscript 'Optimizing one-dose and two-dose cholera vaccine allocation in outbreak settings: A modeling study.' has been provisionally accepted for publication in PLOS Neglected Tropical Diseases.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

James Michael Fleckenstein, M.D.

Associate Editor

PLOS Neglected Tropical Diseases

Sharon Tennant

Deputy Editor

PLOS Neglected Tropical Diseases

***********************************************************

PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0010358.r004

Acceptance letter

Sharon M Tennant, James Michael Fleckenstein

14 Apr 2022

Dear Dr. Matrajt,

We are delighted to inform you that your manuscript, "Optimizing one-dose and two-dose cholera vaccine allocation in outbreak settings: A modeling study.," has been formally accepted for publication in PLOS Neglected Tropical Diseases.

We have now passed your article onto the PLOS Production Department who will complete the rest of the publication process. All authors will receive a confirmation email upon publication.

The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any scientific or type-setting errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript. Note: Proofs for Front Matter articles (Editorial, Viewpoint, Symposium, Review, etc...) are generated on a different schedule and may not be made available as quickly.

Soon after your final files are uploaded, the early version of your manuscript will be published online unless you opted out of this process. The date of the early version will be your article's publication date. The final article will be published to the same URL, and all versions of the paper will be accessible to readers.

Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Shaden Kamhawi

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

Paul Brindley

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Appendix. Appendix: The mathematical models.

    (PDF)

    S1 Fig. Optimal vaccine allocation strategies for different goals in Chad over one year using a vaccine that reduces the probability of symptoms upon infection.

    A: total infections. B: symptomatic infections. C: deaths. We considered enough vaccine to cover 10–100% of the population with a single dose.

    (TIF)

    S2 Fig. Optimal vaccine allocation strategies for different goals in Chad over three years using a vaccine that reduces the probability of symptoms upon infection.

    A: total infections. B: symptomatic infections. C: deaths. We considered enough vaccine to cover 10–100% of the population with a single dose.

    (TIF)

    S3 Fig. Reductions in metrics of disease burden from vaccination campaigns in Chad over one year with a vaccine that reduces the probability of symptoms upon infection.

    We considered enough vaccine to cover 10–100% of the population with a single dose.

    (TIF)

    S4 Fig. Reductions in metrics of disease burden from vaccination campaigns in Chad over three years with a vaccine that reduces the probability of symptoms upon infection.

    We considered enough vaccine to cover 10–100% of the population with a single dose.

    (TIF)

    S1 Table. Description of parameters related to the vaccine and disease metrics.

    (PDF)

    Attachment

    Submitted filename: PNTD_Reviewer_Comment.docx

    Attachment

    Submitted filename: response_to_reviewers_2022_Leung.pdf

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting information files.


    Articles from PLoS Neglected Tropical Diseases are provided here courtesy of PLOS

    RESOURCES