Abstract：
OBJECTIVE: Pandemic response in low-income countries (LICs) or settings often suffers from scarce epidemic surveillance and constrained mitigation capacity. The drivers of pandemic burden in such settings, and the impact of limited and delayed interventions remain poorly understood.
METHODS: We analysed COVID-19 seroprevalence and all-cause excess deaths data from the peri-urban district of Kabwe, Zambia between March 2020 and September 2021 with a novel mathematical model. Data encompassed three consecutive waves caused by the wild-type, Beta and Delta variants.
RESULTS: Across all three waves, we estimated a high cumulative attack rate, with 78% (95% credible interval [CrI] 71-85) of the population infected, and a high all-cause excess mortality, at 402 (95% CrI 277-473) deaths per 100,000 people. Ambitiously improving health care to a capacity similar to that in high-income settings could have averted up to 46% (95% CrI 41-53) of accrued excess deaths, if implemented from June 2020 onward. An early and accelerated vaccination rollout could have achieved the highest reductions in deaths. Had vaccination started as in some high-income settings in December 2020 and with the same daily capacity (doses per 100 population), up to 68% (95% CrI 64-71) of accrued excess deaths could have been averted. Slower rollouts would have still averted 62% (95% CrI 58-68), 54% (95% CrI 49-61) or 26% (95% CrI 20-38) of excess deaths if matching the average vaccination capacity of upper-middle-, lower-middle- or LICs, respectively.
CONCLUSIONS: Robust quantitative analyses of pandemic data are of pressing need to inform future global pandemic preparedness commitments.
METHODS: We analysed COVID-19 seroprevalence and all-cause excess deaths data from the peri-urban district of Kabwe, Zambia between March 2020 and September 2021 with a novel mathematical model. Data encompassed three consecutive waves caused by the wild-type, Beta and Delta variants.
RESULTS: Across all three waves, we estimated a high cumulative attack rate, with 78% (95% credible interval [CrI] 71-85) of the population infected, and a high all-cause excess mortality, at 402 (95% CrI 277-473) deaths per 100,000 people. Ambitiously improving health care to a capacity similar to that in high-income settings could have averted up to 46% (95% CrI 41-53) of accrued excess deaths, if implemented from June 2020 onward. An early and accelerated vaccination rollout could have achieved the highest reductions in deaths. Had vaccination started as in some high-income settings in December 2020 and with the same daily capacity (doses per 100 population), up to 68% (95% CrI 64-71) of accrued excess deaths could have been averted. Slower rollouts would have still averted 62% (95% CrI 58-68), 54% (95% CrI 49-61) or 26% (95% CrI 20-38) of excess deaths if matching the average vaccination capacity of upper-middle-, lower-middle- or LICs, respectively.
CONCLUSIONS: Robust quantitative analyses of pandemic data are of pressing need to inform future global pandemic preparedness commitments.
摘要：
目标：低收入国家或地区（LIC）的流行病应对措施往往受到流行病监测不足和缓解能力有限的影响。在这种情况下，大流行负担的驱动因素，有限和延迟干预的影响仍然知之甚少。
方法：我们分析了来自Kabwe郊区的COVID-19血清阳性率和全因超额死亡数据，赞比亚在2020年3月至2021年9月之间建立了一个新的数学模型。数据包含由野生型引起的三个连续波，Beta和Delta变体。
结果：在所有三个波中，我们估计累积攻击率很高，78%(95%可信区间[CrI]71-85)的人群被感染，和高的全因超额死亡率，每100,000人中有402例（95％CrI277-473）死亡。将医疗保健水平提高到与高收入环境相似的能力，可以避免高达46%(95%CrI41-53)的累积超额死亡，如果从2020年6月起实施。早期和加速的疫苗接种推广，相反,本可以实现死亡人数的最高减少。在2020年12月开始接种疫苗，就像在一些高收入地区一样，并且每天的容量相同（每100人的剂量），高达68%(95%CrI64-71)的累积超额死亡本可以避免。较慢的推广仍然可以避免62%(95%CrI58-68)，54%(95%CrI49-61)，或26％（95％CrI20-38）的过量死亡，如果匹配的平均疫苗接种能力，分别,上-中-，中低端，或LIC。
结论：迫切需要对大流行数据进行强有力的定量分析，以便为未来的全球大流行准备承诺提供信息。
方法：我们分析了来自Kabwe郊区的COVID-19血清阳性率和全因超额死亡数据，赞比亚在2020年3月至2021年9月之间建立了一个新的数学模型。数据包含由野生型引起的三个连续波，Beta和Delta变体。
结果：在所有三个波中，我们估计累积攻击率很高，78%(95%可信区间[CrI]71-85)的人群被感染，和高的全因超额死亡率，每100,000人中有402例（95％CrI277-473）死亡。将医疗保健水平提高到与高收入环境相似的能力，可以避免高达46%(95%CrI41-53)的累积超额死亡，如果从2020年6月起实施。早期和加速的疫苗接种推广，相反,本可以实现死亡人数的最高减少。在2020年12月开始接种疫苗，就像在一些高收入地区一样，并且每天的容量相同（每100人的剂量），高达68%(95%CrI64-71)的累积超额死亡本可以避免。较慢的推广仍然可以避免62%(95%CrI58-68)，54%(95%CrI49-61)，或26％（95％CrI20-38）的过量死亡，如果匹配的平均疫苗接种能力，分别,上-中-，中低端，或LIC。
结论：迫切需要对大流行数据进行强有力的定量分析，以便为未来的全球大流行准备承诺提供信息。
